Nothing
R/locfit.r
In locfit: Local Regression, Likelihood and Density Estimation
"locfit"<-
function(formula, data = sys.frame(sys.parent()), weights = 1, cens = 0, base = 0, subset,
geth = FALSE, ..., lfproc = locfit.raw)
{
Terms <- terms(formula, data = data)
attr(Terms, "intercept") <- 0
m <- match.call()
m[[1]] <- as.name("model.frame")
z <- pmatch(names(m), c("formula", "data", "weights", "cens", "base",
"subset"))
for(i in length(z):2)
if(is.na(z[i])) m[[i]] <- NULL
frm <- eval(m, sys.frame(sys.parent()))
if (nrow(frm) < 1) stop("fewer than one row in the data")
vnames <- as.character(attributes(Terms)$variables)[-1]
if(attr(Terms, "response")) {
y <- model.extract(frm, "response")
yname <- deparse(formula[[2]])
vnames <- vnames[-1]
}
else {
y <- yname <- NULL
}
x <- as.matrix(frm[, vnames])
if(!inherits(x, "lp")) {
if(length(vnames) == dim(x)[2]) {
dimnames(x) <- list(NULL, vnames)
}
}
if(!missing(weights))
weights <- model.extract(frm, weights)
if(!missing(cens))
cens <- model.extract(frm, cens)
if(!missing(base))
base <- model.extract(frm, base)
ret <- lfproc(x, y, weights = weights, cens = cens, base = base, geth = geth,
...)
if(geth == 0) {
ret$terms <- Terms
ret$call <- match.call()
if(!is.null(yname))
ret$yname <- yname
ret$frame <- sys.frame(sys.parent())
}
ret
}
"locfit.raw"<-
function(x, y, weights = 1, cens = 0, base = 0, scale = FALSE, alpha = 0.7,
deg = 2, kern = "tricube", kt = "sph", acri = "none",
basis = list(NULL), deriv = numeric(0), dc = FALSE, family,
link = "default", xlim, renorm = FALSE, ev = rbox(),
maxk = 100, itype = "default", mint = 20, maxit = 20, debug = 0,
geth = FALSE, sty = "none")
{
if(inherits(x, "lp")) {
alpha <- attr(x, "alpha")
deg <- attr(x, "deg")
sty <- attr(x, "style")
acri <- attr(x, "acri")
scale <- attr(x, "scale")
}
if(!is.matrix(x)) {
vnames <- deparse(substitute(x))
x <- matrix(x, ncol = 1)
d <- 1
}
else {
d <- ncol(x)
if(is.null(dimnames(x)))
vnames <- paste("x", 1:d, sep = "")
else vnames <- dimnames(x)[[2]]
}
n <- nrow(x)
if((!missing(y)) && (!is.null(y))) {
yname <- deparse(substitute(y))
if(missing(family))
family <- if(is.logical(y)) "binomial" else "qgaussian"
}
else {
if(missing(family))
family <- "density"
y <- 0
yname <- family
}
if(!missing(basis)) {
## assign("basis", basis, 1)
deg0 <- deg <- length(basis(matrix(0, nrow = 1, ncol = d), rep(0, d)))
}
if(length(deg) == 1)
deg = c(deg, deg)
xl <- rep(0, 2 * d)
lset <- 0
if(!missing(xlim)) {
xl <- lflim(xlim, vnames, xl)
lset <- 1
}
if(is.character(ev)) {
stop("Character ev argument no longer used.")
}
if(is.numeric(ev)) {
xev <- ev
mg <- length(xev)/d
ev <- list(type = "pres", xev = xev, mg = mg, cut = 0, ll = 0, ur = 0)
if(mg == 0)
stop("Invalid ev argument")
}
fl <- c(rep(ev$ll,length.out=d), rep(ev$ur,length.out=d))
mi <- c(n, 0, deg, d, 0, 0, 0, 0, mint, maxit, renorm, 0, 0, 0, dc, maxk,
debug, geth, 0, !missing(basis))
if(any(is.na(mi)))
print(mi)
if(is.logical(scale))
scale <- 1 - as.numeric(scale)
if(length(scale) == 1)
scale <- rep(scale, d)
if(is.character(deriv))
deriv <- match(deriv, vnames)
alpha <- c(alpha, 0, 0, 0)[1:3]
style <- pmatch(sty, c("none", "z1", "z2", "angle", "left", "right", "cpar"))
if(length(style) == 1)
style <- rep(style, d)
dp <- c(alpha, ev$cut, 0, 0, 0, 0, 0, 0)
size <- .C("guessnv",
lw = integer(7),
evt = as.character(c(ev$type, kt)),
dp = as.numeric(dp),
mi = as.integer(mi),
nvc = integer(5),
mg = as.integer(ev$mg), PACKAGE="locfit")
nvc <- size$nvc
lw <- size$lw
z <- .C("slocfit",
x = as.numeric(x),
y = as.numeric(rep(y, length.out = n)),
cens = as.numeric(rep(cens, length.out = n)),
w = as.numeric(rep(weights, length.out = n)),
base = as.numeric(rep(base, length.out = n)),
lim = as.numeric(c(xl, fl)),
mi = as.integer(size$mi),
dp = as.numeric(size$dp),
strings = c(kern, family, link, itype, acri, kt),
scale = as.numeric(scale),
xev = if(ev$type == "pres") as.numeric(xev) else numeric(d * nvc[1]),
wdes = numeric(lw[1]),
wtre = numeric(lw[2]),
wpc = numeric(lw[4]),
nvc = as.integer(size$nvc),
iwk1 = integer(lw[3]),
iwk2 = integer(lw[7]),
lw = as.integer(lw),
mg = as.integer(ev$mg),
L = numeric(lw[5]),
kap = numeric(lw[6]),
deriv = as.integer(deriv),
nd = as.integer(length(deriv)),
sty = as.integer(style),
# basis = list(basis, lfbas),
PACKAGE="locfit")
nvc <- z$nvc
names(nvc) <- c("nvm", "ncm", "vc", "nv", "nc")
nvm <- nvc["nvm"]
ncm <- nvc["ncm"]
nv <- max(nvc["nv"], 1)
nc <- nvc["nc"]
if(geth == 1)
return(matrix(z$L[1:(nv * n)], ncol = nv))
if(geth == 2)
return(list(const = z$kap, d = d))
if(geth == 3)
return(z$kap)
dp <- z$dp
mi <- z$mi
names(mi) <- c("n", "p", "deg0", "deg", "d", "acri", "ker", "kt", "it",
"mint", "mxit", "renorm", "ev", "tg", "link", "dc", "mk", "debug", "geth",
"pc", "ubas")
names(dp) <- c("nnalph", "fixh", "adpen", "cut", "lk", "df1", "df2", "rv",
"swt", "rsc")
if(geth == 4) {
p <- mi["p"]
return(list(residuals = z$y, var = z$wdes[n * (p + 2) + p * p + (1:n)],
nl.df = dp["df1"] - 2))
}
if(geth == 6)
return(z$L)
if(length(deriv) > 0)
trans <- function(x)
x
else trans <- switch(mi["link"] - 2,
function(x)
x,
exp,
expit,
function(x)
1/x,
function(x)
pmax(x, 0)^2,
function(x)
pmax(sin(x), 0)^2)
t1 <- z$wtre
t2 <- z$iwk1
xev <- z$xev[1:(d * nv)]
if(geth == 7)
return(list(x = xev, y = trans(t1[1:nv])))
coef <- matrix(t1[1:((3 * d + 8) * nvm)], nrow = nvm)[1:nv, ]
if(nv == 1)
coef <- matrix(coef, nrow = 1)
if(geth >= 70) {
data <- list(x = x, y = y, cens = cens, base = base, w = weights)
return(list(xev = matrix(xev, ncol = d, byrow = TRUE), coef = coef[, 1], sd =
coef[, d + 2], lower = z$L[1:nv], upper = z$L[nvm + (1:nv)], trans =
trans, d = d, vnames = vnames, kap = z$kap, data = data, mi = mi))
}
eva <- list(ev = ev, xev = xev, coef = coef, scale = z$scale, pc = z$wpc)
class(eva) <- "lfeval"
if(nc == 0) {
cell <- list(sv = integer(0), ce = integer(0), s = integer(0), lo =
as.integer(rep(0, nv)), hi = as.integer(rep(0, nv)))
}
else {
mvc <- max(nv, nc)
mvcm <- max(nvm, ncm)
vc <- nvc["vc"]
cell <- list(sv = t1[nvm * (3 * d + 8) + 1:nc], ce = t2[1:(vc * nc)], s =
t2[vc * ncm + 1:mvc], lo = t2[vc * ncm + mvcm + 1:mvc], hi = t2[vc * ncm +
2 * mvcm + 1:mvc])
}
ret <- list(eva = eva, cell = cell, terms = NULL, nvc = nvc, box = z$lim[2 *
d + 1:(2 * d)], sty = style, deriv = deriv, mi = mi, dp = dp, trans = trans,
critval = crit(const = c(rep(0, d), 1), d = d), vnames = vnames, yname =
yname, call = match.call(), frame = sys.frame(sys.parent()))
class(ret) <- "locfit"
ret
}
"ang" <-
function(x, ...)
{
ret <- lp(x, ..., style = "angle")
dimnames(ret) <- list(NULL, deparse(substitute(x)))
ret
}
"gam.lf"<-
function(x, y, w, xeval, ...)
{
if(!missing(xeval)) {
fit <- locfit.raw(x, y, weights = w, geth = 5, ...)
return(predict(fit, xeval))
}
ret <- locfit.raw(x, y, weights = w, geth = 4, ...)
names(ret) <- c("residuals", "var", "nl.df")
ret
}
"gam.slist"<-
c("s", "lo", "random", "lf")
"lf"<-
function(..., alpha = 0.7, deg = 2, scale = 1, kern = "tcub", ev = rbox(), maxk
= 100)
{
if(!any(gam.slist == "lf"))
warning("gam.slist does not include \"lf\" -- fit will be incorrect")
x <- cbind(...)
scall <- deparse(sys.call())
attr(x, "alpha") <- alpha
attr(x, "deg") <- deg
attr(x, "scale") <- scale
attr(x, "kern") <- kern
attr(x, "ev") <- ev
attr(x, "maxk") <- maxk
attr(x, "call") <- substitute(gam.lf(data[[scall]], z, w, alpha = alpha, deg
= deg, scale = scale, kern = kern, ev = ev, maxk = maxk))
attr(x, "class") <- "smooth"
x
}
#"lfbas" <-
#function(dim, indices, tt, ...)
#{
# indices <- indices + 1
# # C starts at 0, S at 1
# x <- cbind(...)[indices, ]
# res <- basis(x, tt)
# as.numeric(t(res))
#}
"left"<-
function(x, ...)
{
ret <- lp(x, ..., style = "left")
dimnames(ret) <- list(NULL, deparse(substitute(x)))
ret
}
"right"<-
function(x, ...)
{
ret <- lp(x, ..., style = "right")
dimnames(ret) <- list(NULL, deparse(substitute(x)))
ret
}
"cpar"<-
function(x, ...)
{
ret <- lp(x, ..., style = "cpar")
dimnames(ret) <- list(NULL, deparse(substitute(x)))
ret
}
"lp"<-
function(..., nn = 0, h = 0, adpen = 0, deg = 2, acri = "none", scale = FALSE,
style = "none")
{
x <- cbind(...)
z <- as.list(match.call())
z[[1]] <- z$nn <- z$h <- z$adpen <- z$deg <- z$acri <- z$scale <- z$style <-
NULL
dimnames(x) <- list(NULL, z)
if(missing(nn) & missing(h) & missing(adpen))
nn <- 0.7
attr(x, "alpha") <- c(nn, h, adpen)
attr(x, "deg") <- deg
attr(x, "acri") <- acri
attr(x, "style") <- style
attr(x, "scale") <- scale
class(x) <- c("lp", class(x))
x
}
"[.lp" <- function (x, ..., drop = FALSE) {
cl <- oldClass(x)
oldClass(x) <- NULL
ats <- attributes(x)
ats$dimnames <- NULL
ats$dim <- NULL
ats$names <- NULL
y <- x[..., drop = drop]
attributes(y) <- c(attributes(y), ats)
oldClass(y) <- cl
y
}
"fitted.locfit"<-
function(object, data = NULL, what = "coef", cv = FALSE, studentize = FALSE,
type = "fit", tr, ...)
{
if(missing(data)) {
data <- if(is.null(object$call$data)) sys.frame(sys.parent()) else eval(object$call$
data)
}
if(missing(tr))
tr <- if((what == "coef") & (type == "fit")) object$trans else function(x)
x
mm <- locfit.matrix(object, data = data)
n <- object$mi["n"]
pred <- .C("sfitted",
x = as.numeric(mm$x),
y = as.numeric(rep(mm$y, length.out = n)),
w = as.numeric(rep(mm$w, length.out = n)),
ce = as.numeric(rep(mm$ce, length.out = n)),
ba = as.numeric(rep(mm$base, length.out = n)),
fit = numeric(n),
cv = as.integer(cv),
st = as.integer(studentize),
xev = as.numeric(object$eva$xev),
coef = as.numeric(object$eva$coef),
sv = as.numeric(object$cell$sv),
ce = as.integer(c(object$cell$ce, object$cell$s, object$cell$lo, object$
cell$hi)),
wpc = as.numeric(object$eva$pc),
scale = as.numeric(object$eva$scale),
nvc = as.integer(object$nvc),
mi = as.integer(object$mi),
dp = as.numeric(object$dp),
mg = as.integer(object$eva$ev$mg),
deriv = as.integer(object$deriv),
nd = as.integer(length(object$deriv)),
sty = as.integer(object$sty),
what = as.character(c(what, type)),
basis = list(eval(object$call$basis)), PACKAGE="locfit")
tr(pred$fit)
}
"formula.locfit"<-
function(x, ...)
x$call$formula
"predict.locfit"<-
function(object, newdata = NULL, where = "fitp", se.fit = FALSE, band = "none",
what = "coef", ...)
{
if((se.fit) && (band == "none"))
band <- "global"
for(i in 1:length(what)) {
pred <- preplot.locfit(object, newdata, where = where, band = band, what =
what[i], ...)
fit <- pred$trans(pred$fit)
if(i == 1)
res <- fit
else res <- cbind(res, fit)
}
if(band == "none")
return(res)
return(list(fit = res, se.fit = pred$se.fit, residual.scale = pred$
residual.scale))
}
"lines.locfit"<-
function(x, m = 100, tr = x$trans, ...)
{
newx <- lfmarg(x, m = m)[[1]]
y <- predict(x, newx, tr = tr)
lines(newx, y, ...)
}
"points.locfit"<-
function(x, tr, ...)
{
d <- x$mi["d"]
p <- x$mi["p"]
nv <- x$nvc["nv"]
if(d == 1) {
if(missing(tr))
tr <- x$trans
x1 <- x$eva$xev
x2 <- x$eva$coef[, 1]
points(x1, tr(x2), ...)
}
if(d == 2) {
xx <- lfknots(x, what = "x")
points(xx[, 1], xx[, 2], ...)
}
}
"print.locfit"<-
function(x, ...)
{
if(!is.null(cl <- x$call)) {
cat("Call:\n")
dput(cl)
}
cat("\n")
cat("Number of observations: ", x$mi["n"], "\n")
cat("Family: ", c("Density", "PP Rate", "Hazard", "Gaussian", "Logistic",
"Poisson", "Gamma", "Geometric", "Circular", "Huber", "Robust Binomial",
"Weibull", "Cauchy")[x$mi["tg"] %% 64], "\n")
cat("Fitted Degrees of freedom: ", round(x$dp["df2"], 3), "\n")
cat("Residual scale: ", signif(sqrt(x$dp["rv"]), 3), "\n")
invisible(x)
}
"residuals.locfit"<-
function(object, data = NULL, type = "deviance", ...)
{
if(missing(data)) {
data <- if(is.null(object$call$data)) sys.frame(sys.parent()) else eval(object$call$
data)
}
fitted.locfit(object, data, ..., type = type)
}
"summary.locfit"<-
function(object, ...)
{
mi <- object$mi
fam <- c("Density Estimation", "Poisson process rate estimation",
"Hazard Rate Estimation", "Local Regression", "Local Likelihood - Binomial",
"Local Likelihood - Poisson", "Local Likelihood - Gamma",
"Local Likelihood - Geometric", "Local Robust Regression")[mi["tg"] %% 64]
estr <- c("Rectangular Tree", "Triangulation", "Data", "Rectangular Grid",
"k-d tree", "k-d centres", "Cross Validation", "User-provided")[mi["ev"]]
ret <- list(call = object$call, fam = fam, n = mi["n"], d = mi["d"], estr =
estr, nv = object$nvc["nv"], deg = mi["deg"], dp = object$dp, vnames =
object$vnames)
class(ret) <- "summary.locfit"
ret
}
"print.summary.locfit"<-
function(x, ...)
{
cat("Estimation type:", x$fam, "\n")
cat("\nCall:\n")
print(x$call)
cat("\nNumber of data points: ", x$n, "\n")
cat("Independent variables: ", x$vnames, "\n")
cat("Evaluation structure:", x$estr, "\n")
cat("Number of evaluation points: ", x$nv, "\n")
cat("Degree of fit: ", x$deg, "\n")
cat("Fitted Degrees of Freedom: ", round(x$dp["df2"], 3), "\n")
invisible(x)
}
"rbox"<-
function(cut = 0.8, type = "tree", ll = rep(0, 10), ur = rep(0, 10))
{
if(!any(type == c("tree", "kdtree", "kdcenter", "phull")))
stop("Invalid type argument")
ret <- list(type = type, xev = 0, mg = 0, cut = as.numeric(cut), ll =
as.numeric(ll), ur = as.numeric(ur))
class(ret) <- "lf_evs"
ret
}
"lfgrid"<-
function(mg = 10, ll = rep(0, 10), ur = rep(0, 10))
{
if(length(mg) == 1)
mg <- rep(mg, 10)
ret <- list(type = "grid", xev = 0, mg = as.integer(mg), cut = 0, ll =
as.numeric(ll), ur = as.numeric(ur))
class(ret) <- "lf_evs"
ret
}
"dat"<-
function(cv = FALSE)
{
type <- if(cv) "crossval" else "data"
ret <- list(type = type, xev = 0, mg = 0, cut = 0, ll = 0, ur = 0)
class(ret) <- "lf_evs"
ret
}
"xbar"<-
function()
{
ret <- list(type = "xbar", xev = 0, mg = 0, cut = 0, ll = 0, ur = 0)
class(ret) <- "lf_evs"
ret
}
"none"<-
function()
{
ret <- list(type = "none", xev = 0, mg = 0, cut = 0, ll = 0, ur = 0)
class(ret) <- "lf_evs"
ret
}
"plot.locfit"<-
function(x, xlim, pv, tv, m, mtv = 6, band = "none", tr = NULL, what = "coef",
get.data = FALSE, f3d = (d == 2) && (length(tv) > 0), ...)
{
d <- x$mi["d"]
ev <- x$mi["ev"]
where <- "grid"
if(missing(pv))
pv <- if(d == 1) 1 else c(1, 2)
if(is.character(pv))
pv <- match(pv, x$vnames)
if(missing(tv))
tv <- (1:d)[ - pv]
if(is.character(tv))
tv <- match(tv, x$vnames)
vrs <- c(pv, tv)
if(any(duplicated(vrs)))
warning("Duplicated variables in pv, tv")
if(any((vrs <= 0) | (vrs > d)))
stop("Invalid variable numbers in pv, tv")
if(missing(m))
m <- if(d == 1) 100 else 40
m <- rep(m, d)
m[tv] <- mtv
xl <- x$box
if(!missing(xlim))
xl <- lflim(xlim, x$vnames, xl)
if((d != 2) & (any(ev == c(3, 7, 8))))
pred <- preplot.locfit(x, where = "fitp", band = band, tr = tr, what = what,
get.data = get.data, f3d = f3d)
else {
marg <- lfmarg(xl, m)
pred <- preplot.locfit(x, marg, band = band, tr = tr, what = what, get.data
= get.data, f3d = f3d)
}
plot(pred, pv = pv, tv = tv, ...)
}
"preplot.locfit"<-
function(object, newdata = NULL, where, tr = NULL, what = "coef", band = "none",
get.data = FALSE, f3d = FALSE, ...)
{
mi <- object$mi
dim <- mi["d"]
ev <- mi["ev"]
nointerp <- any(ev == c(3, 7, 8))
wh <- 1
n <- 1
if(is.null(newdata)) {
if(missing(where))
where <- if(nointerp) "fitp" else "grid"
if(where == "grid")
newdata <- lfmarg(object)
if(any(where == c("fitp", "ev", "fitpoints"))) {
where <- "fitp"
newdata <- lfknots(object, what = "x", delete.pv = FALSE)
}
if(where == "data")
newdata <- locfit.matrix(object)$x
if(where == "vect")
stop("you must give the vector points")
}
else {
where <- "vect"
if(is.data.frame(newdata))
newdata <- as.matrix(model.frame(delete.response(object$terms), newdata))
else if(is.list(newdata))
where <- "grid"
else newdata <- as.matrix(newdata)
}
if(is.null(tr)) {
if(what == "coef")
tr <- object$trans
else tr <- function(x)
x
}
if((nointerp) && (where == "grid") && (dim == 2)) {
nv <- object$nvc["nv"]
x <- object$eva$xev[2 * (1:nv) - 1]
y <- object$eva$xev[2 * (1:nv)]
z <- preplot.locfit.raw(object, 0, "fitp", what, band)$y
# haveAkima <- require(akima)
#if (! haveAkima) stop("The akima package is needed for the interp() function. Please note its no-compercial-use license.")
fhat <- interp::interp(x, y, z, newdata[[1]], newdata[[2]], ncp = 2)$z
}
else {
z <- preplot.locfit.raw(object, newdata, where, what, band)
fhat <- z$y
}
fhat[fhat == 0.1278433] <- NA
band <- pmatch(band, c("none", "global", "local", "prediction"))
if(band > 1)
sse <- z$se
else sse <- numeric(0)
if(where != "grid")
newdata <- list(xev = newdata, where = where)
else newdata$where <- where
data <- if(get.data) locfit.matrix(object) else list()
if((f3d) | (dim > 3))
dim <- 3
ret <- list(xev = newdata, fit = fhat, se.fit = sse, residual.scale = sqrt(
object$dp["rv"]), critval = object$critval, trans = tr, vnames = object$
vnames, yname = object$yname, dim = as.integer(dim), data = data)
class(ret) <- "preplot.locfit"
ret
}
"preplot.locfit.raw"<-
function(object, newdata, where, what, band, ...)
{
wh <- pmatch(where, c("vect", "grid", "data", "fitp"))
switch(wh,
{
mg <- n <- nrow(newdata)
xev <- newdata
}
,
{
xev <- unlist(newdata)
mg <- sapply(newdata, length)
n <- prod(mg)
}
,
{
mg <- n <- object$mi["n"]
xev <- newdata
}
,
{
mg <- n <- object$nvc["nv"]
xev <- newdata
}
)
.C("spreplot",
xev = as.numeric(object$eva$xev),
coef = as.numeric(object$eva$coef),
sv = as.numeric(object$cell$sv),
ce = as.integer(c(object$cell$ce, object$cell$s, object$cell$lo, object$
cell$hi)),
x = as.numeric(xev),
y = numeric(n),
se = numeric(n),
wpc = as.numeric(object$eva$pc),
scale = as.numeric(object$eva$scale),
m = as.integer(mg),
nvc = as.integer(object$nvc),
mi = as.integer(object$mi),
dp = as.numeric(object$dp),
mg = as.integer(object$eva$ev$mg),
deriv = as.integer(object$deriv),
nd = as.integer(length(object$deriv)),
sty = as.integer(object$sty),
wh = as.integer(wh),
what = c(what, band),
bs = list(eval(object$call$basis)), PACKAGE="locfit")
}
"print.preplot.locfit"<-
function(x, ...)
{
print(x$trans(x$fit))
invisible(x)
}
"plot.locfit.1d"<-
function(x, add=FALSE, main="", xlab="default", ylab=x$yname, type="l",
ylim, lty = 1, col = 1, ...) {
y <- x$fit
nos <- !is.na(y)
xev <- x$xev[[1]][nos]
y <- y[nos]
ord <- order(xev)
if(xlab == "default")
xlab <- x$vnames
tr <- x$trans
yy <- tr(y)
if(length(x$se.fit) > 0) {
crit <- x$critval$crit.val
cup <- tr((y + crit * x$se.fit))[ord]
clo <- tr((y - crit * x$se.fit))[ord]
}
ndat <- 0
if(length(x$data) > 0) {
ndat <- nrow(x$data$x)
xdsc <- rep(x$data$sc, length.out = ndat)
xdyy <- rep(x$data$y, length.out = ndat)
dok <- xdsc > 0
}
if(missing(ylim)) {
if(length(x$se.fit) > 0)
ylim <- c(min(clo), max(cup))
else ylim <- range(yy)
if(ndat > 0)
ylim <- range(c(ylim, xdyy[dok]/xdsc[dok]))
}
if(!add) {
plot(xev[ord], yy[ord], type = "n", xlab = xlab, ylab = ylab, main = main,
xlim = range(x$xev[[1]]), ylim = ylim, ...)
}
lines(xev[ord], yy[ord], type = type, lty = lty, col = col)
if(length(x$se.fit) > 0) {
lines(xev[ord], cup, lty = 2)
lines(xev[ord], clo, lty = 2)
}
if(ndat > 0) {
xd <- x$data$x[dok]
yd <- xdyy[dok]/xdsc[dok]
cd <- rep(x$data$ce, length.out = ndat)[dok]
if(length(x$data$y) < 2) {
rug(xd[cd == 0])
if(any(cd == 1))
rug(xd[cd == 1], ticksize = 0.015)
}
else {
plotbyfactor(xd, yd, cd, col = col, pch = c("o", "+"), add = TRUE)
}
}
invisible(NULL)
}
"plot.locfit.2d"<-
function(x, type="contour", main, xlab, ylab, zlab=x$yname, ...)
{
if(x$xev$where != "grid")
stop("Can only plot from grids")
if(missing(xlab))
xlab <- x$vnames[1]
if(missing(ylab))
ylab <- x$vnames[2]
tr <- x$trans
m1 <- x$xev[[1]]
m2 <- x$xev[[2]]
y <- matrix(tr(x$fit))
if(type == "contour")
contour(m1, m2, matrix(y, nrow = length(m1)), ...)
if(type == "image")
image(m1, m2, matrix(y, nrow = length(m1)), ...)
if((length(x$data) > 0) && any(type == c("contour", "image"))) {
xd <- x$data$x
ce <- rep(x$data$ce, length.out = nrow(xd))
points(xd[ce == 0, 1], xd[ce == 0, 2], pch = "o")
if(any(ce == 1))
points(xd[ce == 1, 1], xd[ce == 1, 2], pch = "+")
}
if(type == "persp") {
nos <- is.na(y)
y[nos] <- min(y[!nos])
persp(m1, m2, matrix(y, nrow = length(m1)), zlab=zlab, ...)
}
if(!missing(main))
title(main = main)
invisible(NULL)
}
"plot.locfit.3d"<-
function(x, main = "", pv, tv, type = "level", pred.lab = x$vnames, resp.lab =
x$yname, crit = 1.96, ...)
{
xev <- x$xev
if(xev$where != "grid")
stop("Can only plot from grids")
xev$where <- NULL
newx <- as.matrix(expand.grid(xev))
newy <- x$trans(x$fit)
wh <- rep("f", length(newy))
if(length(x$data) > 0) {
dat <- x$data
for(i in tv) {
m <- xev[[i]]
dat$x[, i] <- m[1 + round((dat$x[, i] - m[1])/(m[2] - m[1]))]
}
newx <- rbind(newx, dat$x)
if(is.null(dat$y))
newy <- c(newy, rep(NA, nrow(dat$x)))
else {
newy <- c(newy, dat$y/dat$sc)
newy[is.na(newy)] <- 0
}
wh <- c(wh, rep("d", nrow(dat$x)))
}
if(length(tv) == 0) {
newdat <- data.frame(newy, newx[, pv])
names(newdat) <- c("y", paste("pv", 1:length(pv), sep = ""))
}
else {
newdat <- data.frame(newx[, tv], newx[, pv], newy)
names(newdat) <- c(paste("tv", 1:length(tv), sep = ""), paste("pv", 1:
length(pv), sep = ""), "y")
for(i in 1:length(tv))
newdat[, i] <- as.factor(signif(newdat[, i], 5))
}
loc.strip <- function(...)
strip.default(..., strip.names = c(TRUE, TRUE), style = 1)
if(length(pv) == 1) {
clo <- cup <- numeric(0)
if(length(x$se.fit) > 0) {
if((!is.null(class(crit))) && (inherits(crit, "kappa")))
crit <- crit$crit.val
cup <- x$trans((x$fit + crit * x$se.fit))
clo <- x$trans((x$fit - crit * x$se.fit))
}
formula <- switch(1 + length(tv),
y ~ pv1,
y ~ pv1 | tv1,
y ~ pv1 | tv1 * tv2,
y ~ pv1 | tv1 * tv2 * tv3)
pl <- xyplot(formula, xlab = pred.lab[pv], ylab = resp.lab, main = main,
type = "l", cup = cup, wh = wh, panel = panel.xyplot.lf, data
= newdat, strip = loc.strip, ...)
}
if(length(pv) == 2) {
formula <- switch(1 + length(tv),
y ~ pv1 * pv2,
y ~ pv1 * pv2 | tv1,
y ~ pv1 * pv2 | tv1 * tv2,
y ~ pv1 * pv2 | tv1 * tv2 * tv3)
if(type == "contour")
pl <- contourplot(formula, xlab = pred.lab[pv[1]], ylab = pred.lab[pv[2]],
main = main, data = newdat, strip = loc.strip, ...)
if(type == "level")
pl <- levelplot(formula, xlab = pred.lab[pv[1]], ylab = pred.lab[pv[2]],
main = main, data = newdat, strip = loc.strip, ...)
if((type == "persp") | (type == "wireframe"))
pl <- wireframe(formula, xlab = pred.lab[pv[1]], ylab = pred.lab[pv[2]],
zlab = resp.lab, data = newdat, strip = loc.strip, ...)
}
if(length(tv) > 0) {
## if(exists("is.R") && is.function(is.R) && is.R())
names(pl$cond) <- pred.lab[tv]
## else names(attr(pl$glist, "endpts")) <- attr(pl$glist, "names") <- names(
## attr(pl$glist, "index")) <- pred.lab[tv]
}
pl
}
"panel.xyplot.lf"<-
function(x, y, subscripts, clo, cup, wh, type = "l", ...)
{
wh <- wh[subscripts]
panel.xyplot(x[wh == "f"], y[wh == "f"], type = type, ...)
if(length(clo) > 0) {
panel.xyplot(x[wh == "f"], clo[subscripts][wh == "f"], type = "l", lty = 2,
...)
panel.xyplot(x[wh == "f"], cup[subscripts][wh == "f"], type = "l", lty = 2,
...)
}
if(any(wh == "d")) {
yy <- y[wh == "d"]
if(any(is.na(yy)))
rug(x[wh == "d"])
else panel.xyplot(x[wh == "d"], yy)
}
}
"plot.preplot.locfit"<-
function(x, pv, tv, ...)
{
if(x$dim == 1)
plot.locfit.1d(x, ...)
if(x$dim == 2)
plot.locfit.2d(x, ...)
if(x$dim >= 3)
print(plot.locfit.3d(x, pv=pv, tv=tv, ...))
invisible(NULL)
}
"summary.preplot.locfit"<-
function(object, ...)
object$trans(object$fit)
## Deepayan Sarkar's patched version:
"panel.locfit"<-
function(x, y, subscripts, z, rot.mat, distance, shade,
light.source, xlim, ylim, zlim, xlim.scaled, ylim.scaled, zlim.scaled, region,
col, lty, lwd, alpha, col.groups, polynum, drape, at,
xlab, ylab, zlab, xlab.default, ylab.default, zlab.default, aspect, panel.aspect,
scales.3d, contour, labels, ...)
{
if(!missing(z)) {
zs <- z[subscripts]
fit <- locfit.raw(cbind(x, y), zs, ...)
marg <- lfmarg(fit, m = 10)
zp <- predict(fit, marg)
if(!missing(contour)) {
#print("contour")
#print(range(zp))
#lattice::render.contour.trellis(marg[[1]], marg[[2]], zp, at = at)
lattice::panel.contourplot(marg[[1]], marg[[2]], zp, 1:length(zp), at=at)
}
else {
# loc.dat <-
# cbind(as.matrix(expand.grid(x = marg[[1]],
# y = marg[[1]])),
# z = zp)
# lattice::render.3d.trellis(cbind(x = x, y = y, z = z[subscripts]),
# type = "cloud",
# xyz.labs = xyz.labs,
# xyz.axes = xyz.axes,
# xyz.mid = xyz.mid,
# xyz.minmax = xyz.minmax,
# xyz.range = xyz.range,
# col.regions = col.regions,
# at = at,
# drape = drape)
lattice::panel.wireframe(marg[[1]], marg[[2]], zp,
rot.mat, distance, shade,
light.source, xlim, ylim, zlim,
xlim.scaled, ylim.scaled, zlim.scaled,
col, lty, lwd, alpha, col.groups, polynum, drape, at)
}
}
else {
panel.xyplot(x, y, ...)
args <- list(x = x, y = y, ...)
ok <- names(formals(locfit.raw))
llines.locfit(do.call("locfit.raw",
args[ok[ok %in% names(args)]]))
}
}
llines.locfit <-
function (x, m = 100, tr = x$trans, ...)
{
newx <- lfmarg(x, m = m)[[1]]
y <- predict(x, newx, tr = tr)
llines(newx, y, ...)
}
## "panel.locfit"<-
# function(x, y, subscripts, z, xyz.labs, xyz.axes, xyz.mid, xyz.minmax,
# xyz.range, col.regions, at, drape, contour, region, groups, ...)
# {
# if(!missing(z)) {
# zs <- z[subscripts]
# fit <- locfit.raw(cbind(x, y), zs, ...)
# marg <- lfmarg(fit, m = 10)
# zp <- predict(fit, marg)
# if(!missing(contour)) {
# print("contour")
# print(range(zp))
# render.contour.trellis(marg[[1]], marg[[2]], zp, at = at)
# }
# else {
# loc.dat <- cbind(as.matrix(expand.grid(x = marg[[1]], y = marg[[1]])), z
# = zp)
# render.3d.trellis(cbind(x = x, y = y, z = z[subscripts]), type = "cloud",
# xyz.labs = xyz.labs, xyz.axes = xyz.axes, xyz.mid = xyz.mid, xyz.minmax
# = xyz.minmax, xyz.range = xyz.range, col.regions = col.regions, at =
# at, drape = drape)
# }
# }
# else {
# panel.xyplot(x, y)
# lines(locfit.raw(x, y, ...))
# }
# }
"lfmarg"<-
function(xlim, m = 40)
{
if(!is.numeric(xlim)) {
d <- xlim$mi["d"]
xlim <- xlim$box
}
else d <- length(m)
marg <- vector("list", d)
m <- rep(m, length.out = d)
for(i in 1:d)
marg[[i]] <- seq(xlim[i], xlim[i + d], length.out = m[i])
marg
}
"lfeval"<-
function(object)
object$eva
"plot.lfeval"<-
function(x, add = FALSE, txt = FALSE, ...)
{
if(inherits(x, "locfit"))
x <- x$eva
d <- length(x$scale)
v <- matrix(x$xev, nrow = d)
if(d == 1) {
xx <- v[1, ]
y <- x$coef[, 1]
}
if(d == 2) {
xx <- v[1, ]
y <- v[2, ]
}
if(!add) {
plot(xx, y, type = "n", ...)
}
points(xx, y, ...)
if(txt)
text(xx, y, (1:length(xx)) - 1)
invisible(x)
}
"print.lfeval"<-
function(x, ...)
{
if(inherits(x, "locfit"))
x <- x$eva
d <- length(x$scale)
ret <- matrix(x$xev, ncol = d, byrow = TRUE)
print(ret)
}
"lflim"<-
function(limits, nm, ret)
{
d <- length(nm)
if(is.numeric(limits))
ret <- limits
else {
z <- match(nm, names(limits))
for(i in 1:d)
if(!is.na(z[i])) ret[c(i, i + d)] <- limits[[z[i]]]
}
as.numeric(ret)
}
"plot.eval"<-
function(x, add = FALSE, text = FALSE, ...)
{
d <- x$mi["d"]
v <- matrix(x$eva$xev, nrow = d)
ev <- x$mi["ev"]
pv <- if(any(ev == c(1, 2))) as.logical(x$cell$s) else rep(FALSE, ncol(v))
if(!add) {
plot(v[1, ], v[2, ], type = "n", xlab = x$vnames[1], ylab = x$vnames[2])
}
if(text)
text(v[1, ], v[2, ], (1:x$nvc["nv"]) - 1)
else {
if(any(!pv))
points(v[1, !pv], v[2, !pv], ...)
if(any(pv))
points(v[1, pv], v[2, pv], pch = "*", ...)
}
if(any(x$mi["ev"] == c(1, 2))) {
zz <- .C("triterm",
as.numeric(v),
h = as.numeric(lfknots(x, what = "h", delete.pv = FALSE)),
as.integer(x$cell$ce),
lo = as.integer(x$cell$lo),
hi = as.integer(x$cell$hi),
as.numeric(x$eva$scale),
as.integer(x$nvc),
as.integer(x$mi),
as.numeric(x$dp),
nt = integer(1),
term = integer(600),
box = x$box, PACKAGE="locfit")
ce <- zz$term + 1
}
else ce <- x$cell$ce + 1
if(any(x$mi["ev"] == c(1, 5, 7))) {
vc <- 2^d
ce <- matrix(ce, nrow = vc)
segments(v[1, ce[1, ]], v[2, ce[1, ]], v[1, ce[2, ]], v[2, ce[2, ]],
...)
segments(v[1, ce[1, ]], v[2, ce[1, ]], v[1, ce[3, ]], v[2, ce[3, ]],
...)
segments(v[1, ce[2, ]], v[2, ce[2, ]], v[1, ce[4, ]], v[2, ce[4, ]],
...)
segments(v[1, ce[3, ]], v[2, ce[3, ]], v[1, ce[4, ]], v[2, ce[4, ]],
...)
}
if(any(x$mi["ev"] == c(2, 8))) {
vc <- d + 1
m <- matrix(ce, nrow = 3)
segments(v[1, m[1, ]], v[2, m[1, ]], v[1, m[2, ]], v[2, m[2, ]], ...)
segments(v[1, m[1, ]], v[2, m[1, ]], v[1, m[3, ]], v[2, m[3, ]], ...)
segments(v[1, m[2, ]], v[2, m[2, ]], v[1, m[3, ]], v[2, m[3, ]], ...)
}
invisible(NULL)
}
"rv"<-
function(fit)
fit$dp["rv"]
"rv<-"<-
function(fit, value)
{
fit$dp["rv"] <- value
fit
}
"regband"<-
function(formula, what = c("CP", "GCV", "GKK", "RSW"), deg = 1, ...)
{
m <- match.call()
m$geth <- 3
m$deg <- c(deg, 4)
m$what <- NULL
m$deriv <- match(what, c("CP", "GCV", "GKK", "RSW"))
m[[1]] <- as.name("locfit")
z <- eval(m, sys.frame(sys.parent()))
names(z) <- what
z[1:length(what)]
}
"kdeb"<-
function(x, h0 = 0.01 * sd, h1 = sd, meth = c("AIC", "LCV", "LSCV", "BCV",
"SJPI", "GKK"), kern = "gauss", gf = 2.5)
{
n <- length(x)
sd <- sqrt(var(x))
z <- .C("kdeb",
x = as.numeric(x),
mi = as.integer(n),
band = numeric(length(meth)),
ind = integer(n),
h0 = as.numeric(gf * h0),
h1 = as.numeric(gf * h1),
meth = as.integer(match(meth, c("AIC", "LCV", "LSCV", "BCV", "SJPI", "GKK")
)),
nmeth = as.integer(length(meth)),
kern = pmatch(kern, c("rect", "epan", "bisq", "tcub", "trwt", "gauss")),
PACKAGE="locfit")
band <- z$band
names(band) <- meth
band
}
"lfknots"<-
function(x, tr, what = c("x", "coef", "h", "nlx"), delete.pv = TRUE)
{
nv <- x$nvc["nv"]
d <- x$mi["d"]
p <- x$mi["p"]
z <- 0:(nv - 1)
ret <- matrix(0, nrow = nv, ncol = 1)
rname <- character(0)
if(missing(tr))
tr <- x$trans
coef <- x$eva$coef
for(wh in what) {
if(wh == "x") {
ret <- cbind(ret, matrix(x$eva$xev, ncol = d, byrow = TRUE))
rname <- c(rname, x$vnames)
}
if(wh == "coef") {
d0 <- coef[, 1]
d0[d0 == 0.1278433] <- NA
ret <- cbind(ret, tr(d0))
rname <- c(rname, "mu hat")
}
if(wh == "f1") {
ret <- cbind(ret, coef[, 1 + (1:d)])
rname <- c(rname, paste("d", 1:d, sep = ""))
}
if(wh == "nlx") {
ret <- cbind(ret, coef[, d + 2])
rname <- c(rname, "||l(x)||")
}
if(wh == "nlx1") {
ret <- cbind(ret, coef[, d + 2 + (1:d)])
rname <- c(rname, paste("nlx-d", 1:d, sep = ""))
}
if(wh == "se") {
ret <- cbind(ret, sqrt(x$dp["rv"]) * coef[, d + 2])
rname <- c(rname, "StdErr")
}
if(wh == "infl") {
z <- coef[, 2 * d + 3]
ret <- cbind(ret, z * z)
rname <- c(rname, "Influence")
}
if(wh == "infla") {
ret <- cbind(ret, coef[, 2 * d + 3 + (1:d)])
rname <- c(rname, paste("inf-d", 1:d, sep = ""))
}
if(wh == "lik") {
ret <- cbind(ret, coef[, 3 * d + 3 + (1:3)])
rname <- c(rname, c("LocLike", "fit.df", "res.df"))
}
if(wh == "h") {
ret <- cbind(ret, coef[, 3 * d + 7])
rname <- c(rname, "h")
}
if(wh == "deg") {
ret <- cbind(ret, coef[, 3 * d + 8])
rname <- c(rname, "deg")
}
}
ret <- as.matrix(ret[, -1])
if(nv == 1)
ret <- t(ret)
dimnames(ret) <- list(NULL, rname)
if((delete.pv) && (any(x$mi["ev"] == c(1, 2))))
ret <- ret[!as.logical(x$cell$s), ]
ret
}
"locfit.matrix"<-
function(fit, data)
{
m <- fit$call
n <- fit$mi["n"]
y <- ce <- base <- 0
w <- 1
if(m[[1]] == "locfit.raw") {
x <- as.matrix(eval(m$x, fit$frame))
if(!is.null(m$y))
y <- eval(m$y, fit$frame)
if(!is.null(m$weights))
w <- eval(m$weights, fit$frame)
if(!is.null(m$cens))
ce <- eval(m$cens, fit$frame)
if(!is.null(m$base))
base <- eval(m$base, fit$frame)
}
else {
Terms <- terms(as.formula(m$formula))
attr(Terms, "intercept") <- 0
m[[1]] <- as.name("model.frame")
z <- pmatch(names(m), c("formula", "data", "weights", "cens", "base",
"subset"))
for(i in length(z):2)
if(is.na(z[i])) m[[i]] <- NULL
frm <- eval(m, fit$frame)
vnames <- as.character(attributes(Terms)$variables)[-1]
if(attr(Terms, "response")) {
y <- model.extract(frm, "response")
vnames <- vnames[-1]
}
x <- as.matrix(frm[, vnames])
if(any(names(m) == "weights"))
w <- model.extract(frm, weights)
if(any(names(m) == "cens"))
ce <- model.extract(frm, "cens")
if(any(names(m) == "base"))
base <- model.extract(frm, base)
}
sc <- if(any((fit$mi["tg"] %% 64) == c(5:8, 11, 12))) w else 1
list(x = x, y = y, w = w, sc = sc, ce = ce, base = base)
}
"expit"<-
function(x)
{
y <- x
ix <- (x < 0)
y[ix] <- exp(x[ix])/(1 + exp(x[ix]))
y[!ix] <- 1/(1 + exp( - x[!ix]))
y
}
"plotbyfactor"<-
function(x, y, f, data, col = 1:10, pch = "O", add = FALSE, lg, xlab = deparse(
substitute(x)), ylab = deparse(substitute(y)), log = "", ...)
{
if(!missing(data)) {
x <- eval(substitute(x), data)
y <- eval(substitute(y), data)
f <- eval(substitute(f), data)
}
f <- as.factor(f)
if(!add)
plot(x, y, type = "n", xlab = xlab, ylab = ylab, log = log, ...)
lv <- levels(f)
col <- rep(col, length.out = length(lv))
pch <- rep(pch, length.out = length(lv))
for(i in 1:length(lv)) {
ss <- f == lv[i]
if(any(ss))
points(x[ss], y[ss], col = col[i], pch = pch[i])
}
if(!missing(lg))
legend(lg[1], lg[2], legend = levels(f), col = col, pch = paste(pch,
collapse = ""))
}
"hatmatrix"<-
function(formula, dc = TRUE, ...)
{
m <- match.call()
m$geth <- 1
m[[1]] <- as.name("locfit")
z <- eval(m, sys.frame(sys.parent()))
nvc <- z[[2]]
nvm <- nvc[1]
nv <- nvc[4]
matrix(z[[1]], ncol = nvm)[, 1:nv]
}
"locfit.robust"<-
function(x, y, weights, ..., iter = 3)
{
m <- match.call()
if((!is.numeric(x)) && (inherits(x, "formula"))) {
m1 <- m[[1]]
m[[1]] <- as.name("locfit")
m$lfproc <- m1
names(m)[[2]] <- "formula"
return(eval(m, sys.frame(sys.parent())))
}
n <- length(y)
lfr.wt <- rep(1, n)
m[[1]] <- as.name("locfit.raw")
for(i in 0:iter) {
m$weights <- lfr.wt
fit <- eval(m, sys.frame(sys.parent()))
res <- residuals(fit, type = "raw")
s <- median(abs(res))
lfr.wt <- pmax(1 - (res/(6 * s))^2, 0)^2
}
fit
}
"locfit.censor"<-
function(x, y, cens, ..., iter = 3, km = FALSE)
{
m <- match.call()
if((!is.numeric(x)) && (inherits(x, "formula"))) {
m1 <- m[[1]]
m[[1]] <- as.name("locfit")
m$lfproc <- m1
names(m)[[2]] <- "formula"
return(eval(m, sys.frame(sys.parent())))
}
lfc.y <- y
cens <- as.logical(cens)
m$cens <- m$iter <- m$km <- NULL
m[[1]] <- as.name("locfit.raw")
for (i in 0:iter) {
m$y <- lfc.y
fit <- eval(m, sys.frame(sys.parent()))
fh <- fitted(fit)
if(km) {
sr <- y - fh
lfc.y <- y + km.mrl(sr, cens)
}
else {
rdf <- sum(1 - cens) - 2 * fit$dp["df1"] + fit$dp["df2"]
sigma <- sqrt(sum((y - fh) * (lfc.y - fh))/rdf)
sr <- (y - fh)/sigma
lfc.y <- fh + (sigma * dnorm(sr))/pnorm( - sr)
}
lfc.y[!cens] <- y[!cens]
}
m$cens <- substitute(cens)
m$y <- substitute(y)
fit$call <- m
fit
}
"km.mrl"<-
function(times, cens)
{
n <- length(times)
if(length(cens) != length(times))
stop("times and cens must have equal length")
ord <- order(times)
times <- times[ord]
cens <- cens[ord]
n.alive <- n:1
haz.km <- (1 - cens)/n.alive
surv.km <- exp(cumsum(log(1 - haz.km[ - n])))
int.surv <- c(diff(times) * surv.km)
mrl.km <- c(rev(cumsum(rev(int.surv)))/surv.km, 0)
mrl.km[!cens] <- 0
mrl.km.ord <- numeric(n)
mrl.km.ord[ord] <- mrl.km
mrl.km.ord
}
"locfit.quasi"<-
function(x, y, weights, ..., iter = 3, var = abs)
{
m <- match.call()
if((!is.numeric(x)) && (inherits(x, "formula"))) {
m1 <- m[[1]]
m[[1]] <- as.name("locfit")
m$lfproc <- m1
names(m)[[2]] <- "formula"
return(eval(m, sys.frame(sys.parent())))
}
n <- length(y)
w0 <- lfq.wt <- if(missing(weights)) rep(1, n) else weights
m[[1]] <- as.name("locfit.raw")
for(i in 0:iter) {
m$weights <- lfq.wt
fit <- eval(m, sys.frame(sys.parent()))
fh <- fitted(fit)
lfq.wt <- w0/var(fh)
}
fit
}
"density.lf"<-
function(x, n=50, window="gaussian", width, from, to, cut=if(iwindow == 4)
0.75 else 0.5, ev=lfgrid(mg=n, ll=from, ur=to), deg=0,
family="density", link="ident", ...)
{
if(!exists("logb"))
logb <- log
# for R
x <- sort(x)
r <- range(x)
iwindow <- pmatch(window, c("rectangular", "triangular", "cosine", "gaussian"
), -1.)
if(iwindow < 0.)
kern <- window
else kern <- c("rect", "tria", NA, "gauss")[iwindow]
if(missing(width)) {
nbar <- logb(length(x), base = 2.) + 1.
width <- diff(r)/nbar * 0.5
}
if(missing(from))
from <- r[1.] - width * cut
if(missing(to))
to <- r[2.] + width * cut
if(to <= from)
stop("Invalid from/to values")
h <- width/2
if(kern == "gauss")
h <- h * 1.25
fit <- locfit.raw(lp(x, h = h, deg = deg), ev = ev, kern = kern, link = link,
family = family, ...)
list(x = fit$eva$xev, y = fit$eva$coef[, 1])
}
"smooth.lf"<-
function(x, y, xev = x, direct = FALSE, ...)
{
# just a simple smooth with (x,y) input, mu-hat output.
# locfit.raw options are valid.
if(missing(y)) {
y <- x
x <- 1:length(y)
}
if(direct) {
fit <- locfit.raw(x, y, ev = xev, geth = 7, ...)
fv <- fit$y
xev <- fit$x
if(is.matrix(x))
xev <- matrix(xev, ncol = ncol(x), byrow = TRUE)
}
else {
fit <- locfit.raw(x, y, ...)
fv <- predict(fit, xev)
}
list(x = xev, y = fv, call = match.call())
}
"gcv"<-
function(x, ...)
{
m <- match.call()
if(is.numeric(x))
m[[1]] <- as.name("locfit.raw")
else {
m[[1]] <- as.name("locfit")
names(m)[2] <- "formula"
}
fit <- eval(m, sys.frame(sys.parent()))
z <- fit$dp[c("lk", "df1", "df2")]
n <- fit$mi["n"]
z <- c(z, (-2 * n * z[1])/(n - z[2])^2)
names(z) <- c("lik", "infl", "vari", "gcv")
z
}
"gcvplot"<-
function(..., alpha, df = 2)
{
m <- match.call()
m[[1]] <- as.name("gcv")
m$df <- NULL
if(!is.matrix(alpha))
alpha <- matrix(alpha, ncol = 1)
k <- nrow(alpha)
z <- matrix(nrow = k, ncol = 4)
for(i in 1:k) {
m$alpha <- alpha[i, ]
z[i, ] <- eval(m, sys.frame(sys.parent()))
}
ret <- list(alpha = alpha, cri = "GCV", df = z[, df], values = z[, 4])
class(ret) <- "gcvplot"
ret
}
"plot.gcvplot"<-
function(x, xlab = "Fitted DF", ylab = x$cri, ...)
{
plot(x$df, x$values, xlab = xlab, ylab = ylab, ...)
}
"print.gcvplot"<-
function(x, ...)
plot.gcvplot(x = x, ...)
"summary.gcvplot"<-
function(object, ...)
{
z <- cbind(object$df, object$values)
dimnames(z) <- list(NULL, c("df", object$cri))
z
}
"aic"<-
function(x, ..., pen = 2)
{
m <- match.call()
if(is.numeric(x))
m[[1]] <- as.name("locfit.raw")
else {
m[[1]] <- as.name("locfit")
names(m)[2] <- "formula"
}
m$pen <- NULL
fit <- eval(m, sys.frame(sys.parent()))
dp <- fit$dp
z <- dp[c("lk", "df1", "df2")]
z <- c(z, -2 * z[1] + pen * z[2])
names(z) <- c("lik", "infl", "vari", "aic")
z
}
"aicplot"<-
function(..., alpha)
{
m <- match.call()
m[[1]] <- as.name("aic")
if(!is.matrix(alpha))
alpha <- matrix(alpha, ncol = 1)
k <- nrow(alpha)
z <- matrix(nrow = k, ncol = 4)
for(i in 1:k) {
m$alpha <- alpha[i, ]
z[i, ] <- eval(m, sys.frame(sys.parent()))
}
ret <- list(alpha = alpha, cri = "AIC", df = z[, 2], values = z[, 4])
class(ret) <- "gcvplot"
ret
}
"cp"<-
function(x, ..., sig2 = 1)
{
m <- match.call()
if(is.numeric(x))
m[[1]] <- as.name("locfit.raw")
else {
m[[1]] <- as.name("locfit")
names(m)[2] <- "formula"
}
m$sig2 <- NULL
fit <- eval(m, sys.frame(sys.parent()))
z <- c(fit$dp[c("lk", "df1", "df2")], fit$mi["n"])
z <- c(z, (-2 * z[1])/sig2 - z[4] + 2 * z[2])
names(z) <- c("lik", "infl", "vari", "n", "cp")
z
}
"cpplot"<-
function(..., alpha, sig2)
{
m <- match.call()
m[[1]] <- as.name("cp")
m$sig2 <- NULL
if(!is.matrix(alpha))
alpha <- matrix(alpha, ncol = 1)
k <- nrow(alpha)
z <- matrix(nrow = k, ncol = 5)
for(i in 1:k) {
m$alpha <- alpha[i, ]
z[i, ] <- eval(m, sys.frame(sys.parent()))
}
if(missing(sig2)) {
s <- (1:k)[z[, 3] == max(z[, 3])][1]
sig2 <- (-2 * z[s, 1])/(z[s, 4] - 2 * z[s, 2] + z[s, 3])
}
ret <- list(alpha = alpha, cri = "CP", df = z[, 3], values = (-2 * z[, 1])/
sig2 - z[, 4] + 2 * z[, 2])
class(ret) <- "gcvplot"
ret
}
"lcv"<-
function(x, ...)
{
m <- match.call()
if(is.numeric(x))
m[[1]] <- as.name("locfit.raw")
else {
m[[1]] <- as.name("locfit")
names(m)[2] <- "formula"
}
fit <- eval(m, sys.frame(sys.parent()))
z <- fit$dp[c("lk", "df1", "df2")]
res <- residuals(fit, type = "d2", cv = TRUE)
z <- c(z, sum(res))
names(z) <- c("lik", "infl", "vari", "cv")
z
}
"lcvplot"<-
function(..., alpha)
{
m <- match.call()
m[[1]] <- as.name("lcv")
if(!is.matrix(alpha))
alpha <- matrix(alpha, ncol = 1)
k <- nrow(alpha)
z <- matrix(nrow = k, ncol = 4)
for(i in 1:k) {
m$alpha <- alpha[i, ]
z[i, ] <- eval(m, sys.frame(sys.parent()))
}
ret <- list(alpha = alpha, cri = "LCV", df = z[, 2], values = z[, 4])
class(ret) <- "gcvplot"
ret
}
"lscv"<-
function(x, ..., exact = FALSE)
{
if(exact) {
ret <- lscv.exact(x, ...)
}
else {
m <- match.call()
m$exact <- NULL
if(is.numeric(x))
m[[1]] <- as.name("locfit.raw")
else {
m[[1]] <- as.name("locfit")
names(m)[2] <- "formula"
}
m$geth <- 6
ret <- eval(m, sys.frame(sys.parent()))
}
ret
}
"lscv.exact"<-
function(x, h = 0)
{
if(!is.null(attr(x, "alpha")))
h <- attr(x, "alpha")[2]
if(h <= 0)
stop("lscv.exact: h must be positive.")
ret <- .C("slscv",
x = as.numeric(x),
n = as.integer(length(x)),
h = as.numeric(h),
ret = numeric(2), PACKAGE="locfit")$ret
ret
}
"lscvplot"<-
function(..., alpha)
{
m <- match.call()
m[[1]] <- as.name("lscv")
if(!is.matrix(alpha))
alpha <- matrix(alpha, ncol = 1)
k <- nrow(alpha)
z <- matrix(nrow = k, ncol = 2)
for(i in 1:k) {
m$alpha <- alpha[i, ]
z[i, ] <- eval(m, sys.frame(sys.parent()))
}
ret <- list(alpha = alpha, cri = "LSCV", df = z[, 2], values = z[, 1])
class(ret) <- "gcvplot"
ret
}
"sjpi"<-
function(x, a)
{
dnorms <- function(x, k)
{
if(k == 0)
return(dnorm(x))
if(k == 1)
return( - x * dnorm(x))
if(k == 2)
return((x * x - 1) * dnorm(x))
if(k == 3)
return(x * (3 - x * x) * dnorm(x))
if(k == 4)
return((3 - x * x * (6 - x * x)) * dnorm(x))
if(k == 6)
return((-15 + x * x * (45 - x * x * (15 - x * x))) * dnorm(x))
stop("k too large in dnorms")
}
alpha <- a * sqrt(2)
n <- length(x)
M <- outer(x, x, "-")
s <- numeric(length(alpha))
for(i in 1:length(alpha)) {
s[i] <- sum(dnorms(M/alpha[i], 4))
}
s <- s/(n * (n - 1) * alpha^5)
h <- (s * 2 * sqrt(pi) * n)^(-0.2)
lambda <- diff(summary(x)[c(2, 5)])
A <- 0.92 * lambda * n^(-1/7)
B <- 0.912 * lambda * n^(-1/9)
tb <- - sum(dnorms(M/B, 6))/(n * (n - 1) * B^7)
sa <- sum(dnorms(M/A, 4))/(n * (n - 1) * A^5)
ah <- 1.357 * (sa/tb * h^5)^(1/7)
cbind(h, a, ah/sqrt(2), s)
}
"scb"<-
function(x, ..., ev = lfgrid(20), simul = TRUE, type = 1)
{
oc <- m <- match.call()
if(is.numeric(x))
m[[1]] <- as.name("locfit.raw")
else {
m[[1]] <- as.name("locfit")
names(m)[2] <- "formula"
}
m$type <- m$simul <- NULL
m$geth <- 70 + type + 10 * simul
m$ev <- substitute(ev)
fit <- eval(m, sys.frame(sys.parent()))
fit$call <- oc
class(fit) <- "scb"
fit
}
"plot.scb"<-
function(x, add = FALSE, ...)
{
fit <- x$trans(x$coef)
lower <- x$trans(x$lower)
upper <- x$trans(x$upper)
d <- x$d
if(d == 1)
plot.scb.1d(x, fit, lower, upper, add, ...)
if(d == 2)
plot.scb.2d(x, fit = fit, lower = lower, upper = upper, ...)
if(!any(d == c(1, 2)))
stop("Can't plot this scb")
}
"plot.scb.1d"<-
function(x, fit, lower, upper, add = FALSE, style = "band", ...)
{
if(style == "test") {
lower <- lower - fit
upper <- upper - fit
}
if(!add) {
yl <- range(c(lower, fit, upper))
plot(x$xev, fit, type = "l", ylim = yl, xlab = x$vnames[1])
}
lines(x$xev, lower, lty = 2)
lines(x$xev, upper, lty = 2)
if(is.null(x$call$deriv)) {
dx <- x$data$x
sc <- if(any((x$mi["tg"] %% 64) == c(5:8, 11, 12))) x$data$w else 1
dy <- x$data$y/sc
points(dx, dy)
}
if(style == "test")
abline(h = 0, lty = 3)
}
"plot.scb.2d" <- function(x, fit, lower, upper, style = "tl", ylim, ...) {
plot.tl <- function(x, y, z, nint = c(16, 15), v1, v2,
xlab=deparse(substitute(x)),
ylab=deparse(substitute(y)),
legend=FALSE, pch="", ...) {
xl <- range(x)
if (legend) {
mar <- par()$mar
if (mar[4] < 6.1)
par(mar = c(mar[1:3], 6.1))
on.exit(par(mar = mar))
dlt <- diff(xl)
xl[2] <- xl[2] + 0.02 * dlt
}
plot(1, 1, type = "n", xlim = xl, ylim = range(y), xlab = xlab,
ylab = ylab, ...)
nx <- length(x)
ny <- length(y)
if (missing(v)) {
v <- seq(min(z) - 0.0001, max(z), length.out = nint + 1)
} else {
nint <- length(v) - 1
}
ix <- rep(1:nx, ny)
iy <- rep(1:ny, rep(nx, ny))
r1 <- range(z[, 1])
r2 <- range(z[, 2])
hue <- if (missing(v1)) {
floor((nint[1] * (z[, 1] - r1[1]))/(r1[2] - r1[1]) * 0.999999999)
} else cut(z[, 1], v1) - 1
sat <- if (missing(v2)) {
floor((nint[2] * (z[, 2] - r2[1]))/(r2[2] - r2[1]) * 0.999999999)
} else cut(z[, 2], v2) - 1
col <- hue + nint[1] * sat + 1
x <- c(2 * x[1] - x[2], x, 2 * x[nx] - x[nx - 1])
y <- c(2 * y[1] - y[2], y, 2 * y[ny] - y[ny - 1])
x <- (x[1:(nx + 1)] + x[2:(nx + 2)])/2
y <- (y[1:(ny + 1)] + y[2:(ny + 2)])/2
for (i in unique(col)) {
u <- col == i
if(pch == "") {
xx <- rbind(x[ix[u]], x[ix[u] + 1], x[ix[u] + 1], x[ix[u]], NA)
yy <- rbind(y[iy[u]], y[iy[u]], y[iy[u] + 1], y[iy[u] + 1], NA)
polygon(xx, yy, col = i, border = 0)
}
else points(x[ix[u]], y[iy[u]], col = i, pch = pch)
}
if(legend) {
yv <- seq(min(y), max(y), length = length(v))
x1 <- max(x) + 0.02 * dlt
x2 <- max(x) + 0.06 * dlt
for(i in 1:nint) {
polygon(c(x1, x2, x2, x1), rep(yv[i:(i + 1)], c(2, 2)),
col = i, border = 0)
}
axis(side = 4, at = yv, labels = v, adj = 0)
}
}
if(style == "trell") {
if(missing(ylim))
ylim <- range(c(fit, lower, upper))
loc.dat = data.frame(x1 = x$xev[, 1], x2 = x$xev[, 2], y = fit)
pl <- xyplot(y ~ x1 | as.factor(x2), data = loc.dat,
panel = panel.xyplot.lf, clo=lower, cup=upper,
wh=rep("f", nrow(loc.dat)))
plot(pl)
}
if(style == "tl") {
ux <- unique(x$xev[, 1])
uy <- unique(x$xev[, 2])
sig <- abs(x$coef/x$sd)
rv1 <- max(abs(fit)) * 1.0001
v1 <- seq( - rv1, rv1, length.out = 17)
v2 <- - c(-1e-100, crit(const = x$kap, cov = c(0.5, 0.7, 0.8, 0.85,
0.9, 0.95, 0.98, 0.99, 0.995,
0.999, 0.9999))$crit.val,
1e+300)
plot.tl(ux, uy, cbind(fit, - sig), v1 = v1, v2 = v2,
xlab = x$vnames[1], ylab = x$vnames[2])
}
}
"print.scb"<-
function(x, ...)
{
m <- cbind(x$xev, x$trans(x$coef), x$trans(x$lower), x$trans(x$upper))
dimnames(m) <- list(NULL, c(x$vnames, "fit", "lower", "upper"))
print(m)
}
"kappa0"<-
function(formula, cov=0.95, ev=lfgrid(20), ...)
{
if(inherits(formula, "locfit")) {
m <- formula$call
}
else {
m <- match.call()
m$cov <- NULL
}
m$dc <- TRUE
m$geth <- 2
m$ev <- substitute(ev)
m[[1]] <- as.name("locfit")
z <- eval(m, sys.frame(sys.parent()))
crit(const = z$const, d = z$d, cov = cov)
}
"crit"<-
function(fit, const = c(0, 1), d = 1, cov = 0.95, rdf = 0)
{
if(!missing(fit)) {
z <- fit$critval
if(missing(const) & missing(d) & missing(cov))
return(z)
if(!missing(const))
z$const <- const
if(!missing(d))
z$d <- d
if(!missing(cov))
z$cov <- cov
if(!missing(rdf))
z$rdf <- rdf
}
else {
z <- list(const = const, d = d, cov = cov, rdf = rdf, crit.val = 0)
class(z) <- "kappa"
}
z$crit.val <- .C("scritval",
k0 = as.numeric(z$const),
d = as.integer(z$d),
cov = as.numeric(z$cov),
m = as.integer(length(z$const)),
rdf = as.numeric(z$rdf),
x = numeric(1),
k = as.integer(1), PACKAGE="locfit")$x
z
}
"crit<-"<-
function(fit, value)
{
if(is.numeric(value))
fit$critval$crit.val <- value[1]
else {
if(!inherits(value, "kappa"))
stop("crit<-: value must be numeric or class kappa")
fit$critval <- value
}
fit
}
"spence.15"<-
function(y)
{
n <- length(y)
y <- c(rep(y[1], 7), y, rep(y[n], 7))
n <- length(y)
k <- 3:(n - 2)
a3 <- y[k - 1] + y[k] + y[k + 1]
a2 <- y[k - 2] + y[k + 2]
y1 <- y[k] + 3 * (a3 - a2)
n <- length(y1)
k <- 1:(n - 3)
y2 <- y1[k] + y1[k + 1] + y1[k + 2] + y1[k + 3]
n <- length(y2)
k <- 1:(n - 3)
y3 <- y2[k] + y2[k + 1] + y2[k + 2] + y2[k + 3]
n <- length(y3)
k <- 1:(n - 4)
y4 <- y3[k] + y3[k + 1] + y3[k + 2] + y3[k + 3] + y3[k + 4]
y4/320
}
"spence.21"<-
function(y)
{
n <- length(y)
y <- c(rep(y[1], 10), y, rep(y[n], 10))
n <- length(y)
k <- 4:(n - 3)
y1 <- - y[k - 3] + y[k - 1] + 2 * y[k] + y[k + 1] - y[k + 3]
n <- length(y1)
k <- 4:(n - 3)
y2 <- y1[k - 3] + y1[k - 2] + y1[k - 1] + y1[k] + y1[k + 1] + y1[k + 2] + y1[
k + 3]
n <- length(y2)
k <- 3:(n - 2)
y3 <- y2[k - 2] + y2[k - 1] + y2[k] + y2[k + 1] + y2[k + 2]
n <- length(y3)
k <- 3:(n - 2)
y4 <- y3[k - 2] + y3[k - 1] + y3[k] + y3[k + 1] + y3[k + 2]
y4/350
}
"store"<-
function(data = FALSE, grand = FALSE)
{
lfmod <- c("ang", "gam.lf", "gam.slist", "lf", "left", "right", #"lfbas",
"cpar", "lp")
lfmeth <- c("fitted.locfit", "formula.locfit", "predict.locfit",
"lines.locfit", "points.locfit", "print.locfit", "residuals.locfit",
"summary.locfit", "print.summary.locfit")
lfev <- c("rbox", "gr", "dat", "xbar", "none")
lfplo <- c("plot.locfit", "preplot.locfit", "preplot.locfit.raw",
"print.preplot.locfit", "plot.locfit.1d", "plot.locfit.2d",
"plot.locfit.3d", "panel.xyplot.lf", "plot.preplot.locfit",
"summary.preplot.locfit", "panel.locfit", "lfmarg")
lffre <- c("hatmatrix", "locfit.robust", "locfit.censor", "km.mrl",
"locfit.quasi", "density.lf", "smooth.lf")
lfscb <- c("scb", "plot.scb", "plot.scb.1d", "plot.scb.2d", "print.scb",
"kappa0", "crit", "crit<-", "plot.tl")
lfgcv <- c("gcv", "gcvplot", "plot.gcvplot", "print.gcvplot",
"summary.gcvplot", "aic", "aicplot", "cp", "cpplot", "lcv", "lcvplot",
"lscv", "lscv.exact", "lscvplot", "sjpi")
lfspen <- c("spence.15", "spence.21")
lffuns <- c("locfit", "locfit.raw", lfmod, lfmeth, lfev, lfplo, "lfeval",
"plot.lfeval", "print.lfeval", "lflim", "plot.eval", "rv", "rv<-",
"regband", "kdeb", "lfknots", "locfit.matrix", "expit", "plotbyfactor",
lffre, lfgcv, lfscb, lfspen, "store")
lfdata <- c("bad", "cltest", "cltrain", "co2", "diab", "geyser", "ethanol",
"mcyc", "morths", "border", "heart", "trimod", "insect", "iris", "spencer",
"stamp")
lfgrand <- c("locfit.raw", "crit", "predict.locfit", "preplot.locfit",
"preplot.locfit.raw", "expit", "rv", "rv<-", "knots") #"lfbas"
dump(lffuns, "S/locfit.s")
if(data)
dump(lfdata, "S/locfit.dat")
if(grand)
dump(lfgrand, "src-gr/lfgrand.s")
dump(lffuns, "R/locfit.s")
}
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locfit documentation built on June 24, 2024, 5:08 p.m.
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"locfit"<-
function(formula, data = sys.frame(sys.parent()), weights = 1, cens = 0, base = 0, subset,
geth = FALSE, ..., lfproc = locfit.raw)
{
Terms <- terms(formula, data = data)
attr(Terms, "intercept") <- 0
m <- match.call()
m[[1]] <- as.name("model.frame")
z <- pmatch(names(m), c("formula", "data", "weights", "cens", "base",
"subset"))
for(i in length(z):2)
if(is.na(z[i])) m[[i]] <- NULL
frm <- eval(m, sys.frame(sys.parent()))
if (nrow(frm) < 1) stop("fewer than one row in the data")
vnames <- as.character(attributes(Terms)$variables)[-1]
if(attr(Terms, "response")) {
y <- model.extract(frm, "response")
yname <- deparse(formula[[2]])
vnames <- vnames[-1]
}
else {
y <- yname <- NULL
}
x <- as.matrix(frm[, vnames])
if(!inherits(x, "lp")) {
if(length(vnames) == dim(x)[2]) {
dimnames(x) <- list(NULL, vnames)
}
}
if(!missing(weights))
weights <- model.extract(frm, weights)
if(!missing(cens))
cens <- model.extract(frm, cens)
if(!missing(base))
base <- model.extract(frm, base)
ret <- lfproc(x, y, weights = weights, cens = cens, base = base, geth = geth,
...)
if(geth == 0) {
ret$terms <- Terms
ret$call <- match.call()
if(!is.null(yname))
ret$yname <- yname
ret$frame <- sys.frame(sys.parent())
}
ret
}
"locfit.raw"<-
function(x, y, weights = 1, cens = 0, base = 0, scale = FALSE, alpha = 0.7,
deg = 2, kern = "tricube", kt = "sph", acri = "none",
basis = list(NULL), deriv = numeric(0), dc = FALSE, family,
link = "default", xlim, renorm = FALSE, ev = rbox(),
maxk = 100, itype = "default", mint = 20, maxit = 20, debug = 0,
geth = FALSE, sty = "none")
{
if(inherits(x, "lp")) {
alpha <- attr(x, "alpha")
deg <- attr(x, "deg")
sty <- attr(x, "style")
acri <- attr(x, "acri")
scale <- attr(x, "scale")
}
if(!is.matrix(x)) {
vnames <- deparse(substitute(x))
x <- matrix(x, ncol = 1)
d <- 1
}
else {
d <- ncol(x)
if(is.null(dimnames(x)))
vnames <- paste("x", 1:d, sep = "")
else vnames <- dimnames(x)[[2]]
}
n <- nrow(x)
if((!missing(y)) && (!is.null(y))) {
yname <- deparse(substitute(y))
if(missing(family))
family <- if(is.logical(y)) "binomial" else "qgaussian"
}
else {
if(missing(family))
family <- "density"
y <- 0
yname <- family
}
if(!missing(basis)) {
## assign("basis", basis, 1)
deg0 <- deg <- length(basis(matrix(0, nrow = 1, ncol = d), rep(0, d)))
}
if(length(deg) == 1)
deg = c(deg, deg)
xl <- rep(0, 2 * d)
lset <- 0
if(!missing(xlim)) {
xl <- lflim(xlim, vnames, xl)
lset <- 1
}
if(is.character(ev)) {
stop("Character ev argument no longer used.")
}
if(is.numeric(ev)) {
xev <- ev
mg <- length(xev)/d
ev <- list(type = "pres", xev = xev, mg = mg, cut = 0, ll = 0, ur = 0)
if(mg == 0)
stop("Invalid ev argument")
}
fl <- c(rep(ev$ll,length.out=d), rep(ev$ur,length.out=d))
mi <- c(n, 0, deg, d, 0, 0, 0, 0, mint, maxit, renorm, 0, 0, 0, dc, maxk,
debug, geth, 0, !missing(basis))
if(any(is.na(mi)))
print(mi)
if(is.logical(scale))
scale <- 1 - as.numeric(scale)
if(length(scale) == 1)
scale <- rep(scale, d)
if(is.character(deriv))
deriv <- match(deriv, vnames)
alpha <- c(alpha, 0, 0, 0)[1:3]
style <- pmatch(sty, c("none", "z1", "z2", "angle", "left", "right", "cpar"))
if(length(style) == 1)
style <- rep(style, d)
dp <- c(alpha, ev$cut, 0, 0, 0, 0, 0, 0)
size <- .C("guessnv",
lw = integer(7),
evt = as.character(c(ev$type, kt)),
dp = as.numeric(dp),
mi = as.integer(mi),
nvc = integer(5),
mg = as.integer(ev$mg), PACKAGE="locfit")
nvc <- size$nvc
lw <- size$lw
z <- .C("slocfit",
x = as.numeric(x),
y = as.numeric(rep(y, length.out = n)),
cens = as.numeric(rep(cens, length.out = n)),
w = as.numeric(rep(weights, length.out = n)),
base = as.numeric(rep(base, length.out = n)),
lim = as.numeric(c(xl, fl)),
mi = as.integer(size$mi),
dp = as.numeric(size$dp),
strings = c(kern, family, link, itype, acri, kt),
scale = as.numeric(scale),
xev = if(ev$type == "pres") as.numeric(xev) else numeric(d * nvc[1]),
wdes = numeric(lw[1]),
wtre = numeric(lw[2]),
wpc = numeric(lw[4]),
nvc = as.integer(size$nvc),
iwk1 = integer(lw[3]),
iwk2 = integer(lw[7]),
lw = as.integer(lw),
mg = as.integer(ev$mg),
L = numeric(lw[5]),
kap = numeric(lw[6]),
deriv = as.integer(deriv),
nd = as.integer(length(deriv)),
sty = as.integer(style),
# basis = list(basis, lfbas),
PACKAGE="locfit")
nvc <- z$nvc
names(nvc) <- c("nvm", "ncm", "vc", "nv", "nc")
nvm <- nvc["nvm"]
ncm <- nvc["ncm"]
nv <- max(nvc["nv"], 1)
nc <- nvc["nc"]
if(geth == 1)
return(matrix(z$L[1:(nv * n)], ncol = nv))
if(geth == 2)
return(list(const = z$kap, d = d))
if(geth == 3)
return(z$kap)
dp <- z$dp
mi <- z$mi
names(mi) <- c("n", "p", "deg0", "deg", "d", "acri", "ker", "kt", "it",
"mint", "mxit", "renorm", "ev", "tg", "link", "dc", "mk", "debug", "geth",
"pc", "ubas")
names(dp) <- c("nnalph", "fixh", "adpen", "cut", "lk", "df1", "df2", "rv",
"swt", "rsc")
if(geth == 4) {
p <- mi["p"]
return(list(residuals = z$y, var = z$wdes[n * (p + 2) + p * p + (1:n)],
nl.df = dp["df1"] - 2))
}
if(geth == 6)
return(z$L)
if(length(deriv) > 0)
trans <- function(x)
x
else trans <- switch(mi["link"] - 2,
function(x)
x,
exp,
expit,
function(x)
1/x,
function(x)
pmax(x, 0)^2,
function(x)
pmax(sin(x), 0)^2)
t1 <- z$wtre
t2 <- z$iwk1
xev <- z$xev[1:(d * nv)]
if(geth == 7)
return(list(x = xev, y = trans(t1[1:nv])))
coef <- matrix(t1[1:((3 * d + 8) * nvm)], nrow = nvm)[1:nv, ]
if(nv == 1)
coef <- matrix(coef, nrow = 1)
if(geth >= 70) {
data <- list(x = x, y = y, cens = cens, base = base, w = weights)
return(list(xev = matrix(xev, ncol = d, byrow = TRUE), coef = coef[, 1], sd =
coef[, d + 2], lower = z$L[1:nv], upper = z$L[nvm + (1:nv)], trans =
trans, d = d, vnames = vnames, kap = z$kap, data = data, mi = mi))
}
eva <- list(ev = ev, xev = xev, coef = coef, scale = z$scale, pc = z$wpc)
class(eva) <- "lfeval"
if(nc == 0) {
cell <- list(sv = integer(0), ce = integer(0), s = integer(0), lo =
as.integer(rep(0, nv)), hi = as.integer(rep(0, nv)))
}
else {
mvc <- max(nv, nc)
mvcm <- max(nvm, ncm)
vc <- nvc["vc"]
cell <- list(sv = t1[nvm * (3 * d + 8) + 1:nc], ce = t2[1:(vc * nc)], s =
t2[vc * ncm + 1:mvc], lo = t2[vc * ncm + mvcm + 1:mvc], hi = t2[vc * ncm +
2 * mvcm + 1:mvc])
}
ret <- list(eva = eva, cell = cell, terms = NULL, nvc = nvc, box = z$lim[2 *
d + 1:(2 * d)], sty = style, deriv = deriv, mi = mi, dp = dp, trans = trans,
critval = crit(const = c(rep(0, d), 1), d = d), vnames = vnames, yname =
yname, call = match.call(), frame = sys.frame(sys.parent()))
class(ret) <- "locfit"
ret
}
"ang" <-
function(x, ...)
{
ret <- lp(x, ..., style = "angle")
dimnames(ret) <- list(NULL, deparse(substitute(x)))
ret
}
"gam.lf"<-
function(x, y, w, xeval, ...)
{
if(!missing(xeval)) {
fit <- locfit.raw(x, y, weights = w, geth = 5, ...)
return(predict(fit, xeval))
}
ret <- locfit.raw(x, y, weights = w, geth = 4, ...)
names(ret) <- c("residuals", "var", "nl.df")
ret
}
"gam.slist"<-
c("s", "lo", "random", "lf")
"lf"<-
function(..., alpha = 0.7, deg = 2, scale = 1, kern = "tcub", ev = rbox(), maxk
= 100)
{
if(!any(gam.slist == "lf"))
warning("gam.slist does not include \"lf\" -- fit will be incorrect")
x <- cbind(...)
scall <- deparse(sys.call())
attr(x, "alpha") <- alpha
attr(x, "deg") <- deg
attr(x, "scale") <- scale
attr(x, "kern") <- kern
attr(x, "ev") <- ev
attr(x, "maxk") <- maxk
attr(x, "call") <- substitute(gam.lf(data[[scall]], z, w, alpha = alpha, deg
= deg, scale = scale, kern = kern, ev = ev, maxk = maxk))
attr(x, "class") <- "smooth"
x
}
#"lfbas" <-
#function(dim, indices, tt, ...)
#{
# indices <- indices + 1
# # C starts at 0, S at 1
# x <- cbind(...)[indices, ]
# res <- basis(x, tt)
# as.numeric(t(res))
#}
"left"<-
function(x, ...)
{
ret <- lp(x, ..., style = "left")
dimnames(ret) <- list(NULL, deparse(substitute(x)))
ret
}
"right"<-
function(x, ...)
{
ret <- lp(x, ..., style = "right")
dimnames(ret) <- list(NULL, deparse(substitute(x)))
ret
}
"cpar"<-
function(x, ...)
{
ret <- lp(x, ..., style = "cpar")
dimnames(ret) <- list(NULL, deparse(substitute(x)))
ret
}
"lp"<-
function(..., nn = 0, h = 0, adpen = 0, deg = 2, acri = "none", scale = FALSE,
style = "none")
{
x <- cbind(...)
z <- as.list(match.call())
z[[1]] <- z$nn <- z$h <- z$adpen <- z$deg <- z$acri <- z$scale <- z$style <-
NULL
dimnames(x) <- list(NULL, z)
if(missing(nn) & missing(h) & missing(adpen))
nn <- 0.7
attr(x, "alpha") <- c(nn, h, adpen)
attr(x, "deg") <- deg
attr(x, "acri") <- acri
attr(x, "style") <- style
attr(x, "scale") <- scale
class(x) <- c("lp", class(x))
x
}
"[.lp" <- function (x, ..., drop = FALSE) {
cl <- oldClass(x)
oldClass(x) <- NULL
ats <- attributes(x)
ats$dimnames <- NULL
ats$dim <- NULL
ats$names <- NULL
y <- x[..., drop = drop]
attributes(y) <- c(attributes(y), ats)
oldClass(y) <- cl
y
}
"fitted.locfit"<-
function(object, data = NULL, what = "coef", cv = FALSE, studentize = FALSE,
type = "fit", tr, ...)
{
if(missing(data)) {
data <- if(is.null(object$call$data)) sys.frame(sys.parent()) else eval(object$call$
data)
}
if(missing(tr))
tr <- if((what == "coef") & (type == "fit")) object$trans else function(x)
x
mm <- locfit.matrix(object, data = data)
n <- object$mi["n"]
pred <- .C("sfitted",
x = as.numeric(mm$x),
y = as.numeric(rep(mm$y, length.out = n)),
w = as.numeric(rep(mm$w, length.out = n)),
ce = as.numeric(rep(mm$ce, length.out = n)),
ba = as.numeric(rep(mm$base, length.out = n)),
fit = numeric(n),
cv = as.integer(cv),
st = as.integer(studentize),
xev = as.numeric(object$eva$xev),
coef = as.numeric(object$eva$coef),
sv = as.numeric(object$cell$sv),
ce = as.integer(c(object$cell$ce, object$cell$s, object$cell$lo, object$
cell$hi)),
wpc = as.numeric(object$eva$pc),
scale = as.numeric(object$eva$scale),
nvc = as.integer(object$nvc),
mi = as.integer(object$mi),
dp = as.numeric(object$dp),
mg = as.integer(object$eva$ev$mg),
deriv = as.integer(object$deriv),
nd = as.integer(length(object$deriv)),
sty = as.integer(object$sty),
what = as.character(c(what, type)),
basis = list(eval(object$call$basis)), PACKAGE="locfit")
tr(pred$fit)
}
"formula.locfit"<-
function(x, ...)
x$call$formula
"predict.locfit"<-
function(object, newdata = NULL, where = "fitp", se.fit = FALSE, band = "none",
what = "coef", ...)
{
if((se.fit) && (band == "none"))
band <- "global"
for(i in 1:length(what)) {
pred <- preplot.locfit(object, newdata, where = where, band = band, what =
what[i], ...)
fit <- pred$trans(pred$fit)
if(i == 1)
res <- fit
else res <- cbind(res, fit)
}
if(band == "none")
return(res)
return(list(fit = res, se.fit = pred$se.fit, residual.scale = pred$
residual.scale))
}
"lines.locfit"<-
function(x, m = 100, tr = x$trans, ...)
{
newx <- lfmarg(x, m = m)[[1]]
y <- predict(x, newx, tr = tr)
lines(newx, y, ...)
}
"points.locfit"<-
function(x, tr, ...)
{
d <- x$mi["d"]
p <- x$mi["p"]
nv <- x$nvc["nv"]
if(d == 1) {
if(missing(tr))
tr <- x$trans
x1 <- x$eva$xev
x2 <- x$eva$coef[, 1]
points(x1, tr(x2), ...)
}
if(d == 2) {
xx <- lfknots(x, what = "x")
points(xx[, 1], xx[, 2], ...)
}
}
"print.locfit"<-
function(x, ...)
{
if(!is.null(cl <- x$call)) {
cat("Call:\n")
dput(cl)
}
cat("\n")
cat("Number of observations: ", x$mi["n"], "\n")
cat("Family: ", c("Density", "PP Rate", "Hazard", "Gaussian", "Logistic",
"Poisson", "Gamma", "Geometric", "Circular", "Huber", "Robust Binomial",
"Weibull", "Cauchy")[x$mi["tg"] %% 64], "\n")
cat("Fitted Degrees of freedom: ", round(x$dp["df2"], 3), "\n")
cat("Residual scale: ", signif(sqrt(x$dp["rv"]), 3), "\n")
invisible(x)
}
"residuals.locfit"<-
function(object, data = NULL, type = "deviance", ...)
{
if(missing(data)) {
data <- if(is.null(object$call$data)) sys.frame(sys.parent()) else eval(object$call$
data)
}
fitted.locfit(object, data, ..., type = type)
}
"summary.locfit"<-
function(object, ...)
{
mi <- object$mi
fam <- c("Density Estimation", "Poisson process rate estimation",
"Hazard Rate Estimation", "Local Regression", "Local Likelihood - Binomial",
"Local Likelihood - Poisson", "Local Likelihood - Gamma",
"Local Likelihood - Geometric", "Local Robust Regression")[mi["tg"] %% 64]
estr <- c("Rectangular Tree", "Triangulation", "Data", "Rectangular Grid",
"k-d tree", "k-d centres", "Cross Validation", "User-provided")[mi["ev"]]
ret <- list(call = object$call, fam = fam, n = mi["n"], d = mi["d"], estr =
estr, nv = object$nvc["nv"], deg = mi["deg"], dp = object$dp, vnames =
object$vnames)
class(ret) <- "summary.locfit"
ret
}
"print.summary.locfit"<-
function(x, ...)
{
cat("Estimation type:", x$fam, "\n")
cat("\nCall:\n")
print(x$call)
cat("\nNumber of data points: ", x$n, "\n")
cat("Independent variables: ", x$vnames, "\n")
cat("Evaluation structure:", x$estr, "\n")
cat("Number of evaluation points: ", x$nv, "\n")
cat("Degree of fit: ", x$deg, "\n")
cat("Fitted Degrees of Freedom: ", round(x$dp["df2"], 3), "\n")
invisible(x)
}
"rbox"<-
function(cut = 0.8, type = "tree", ll = rep(0, 10), ur = rep(0, 10))
{
if(!any(type == c("tree", "kdtree", "kdcenter", "phull")))
stop("Invalid type argument")
ret <- list(type = type, xev = 0, mg = 0, cut = as.numeric(cut), ll =
as.numeric(ll), ur = as.numeric(ur))
class(ret) <- "lf_evs"
ret
}
"lfgrid"<-
function(mg = 10, ll = rep(0, 10), ur = rep(0, 10))
{
if(length(mg) == 1)
mg <- rep(mg, 10)
ret <- list(type = "grid", xev = 0, mg = as.integer(mg), cut = 0, ll =
as.numeric(ll), ur = as.numeric(ur))
class(ret) <- "lf_evs"
ret
}
"dat"<-
function(cv = FALSE)
{
type <- if(cv) "crossval" else "data"
ret <- list(type = type, xev = 0, mg = 0, cut = 0, ll = 0, ur = 0)
class(ret) <- "lf_evs"
ret
}
"xbar"<-
function()
{
ret <- list(type = "xbar", xev = 0, mg = 0, cut = 0, ll = 0, ur = 0)
class(ret) <- "lf_evs"
ret
}
"none"<-
function()
{
ret <- list(type = "none", xev = 0, mg = 0, cut = 0, ll = 0, ur = 0)
class(ret) <- "lf_evs"
ret
}
"plot.locfit"<-
function(x, xlim, pv, tv, m, mtv = 6, band = "none", tr = NULL, what = "coef",
get.data = FALSE, f3d = (d == 2) && (length(tv) > 0), ...)
{
d <- x$mi["d"]
ev <- x$mi["ev"]
where <- "grid"
if(missing(pv))
pv <- if(d == 1) 1 else c(1, 2)
if(is.character(pv))
pv <- match(pv, x$vnames)
if(missing(tv))
tv <- (1:d)[ - pv]
if(is.character(tv))
tv <- match(tv, x$vnames)
vrs <- c(pv, tv)
if(any(duplicated(vrs)))
warning("Duplicated variables in pv, tv")
if(any((vrs <= 0) | (vrs > d)))
stop("Invalid variable numbers in pv, tv")
if(missing(m))
m <- if(d == 1) 100 else 40
m <- rep(m, d)
m[tv] <- mtv
xl <- x$box
if(!missing(xlim))
xl <- lflim(xlim, x$vnames, xl)
if((d != 2) & (any(ev == c(3, 7, 8))))
pred <- preplot.locfit(x, where = "fitp", band = band, tr = tr, what = what,
get.data = get.data, f3d = f3d)
else {
marg <- lfmarg(xl, m)
pred <- preplot.locfit(x, marg, band = band, tr = tr, what = what, get.data
= get.data, f3d = f3d)
}
plot(pred, pv = pv, tv = tv, ...)
}
"preplot.locfit"<-
function(object, newdata = NULL, where, tr = NULL, what = "coef", band = "none",
get.data = FALSE, f3d = FALSE, ...)
{
mi <- object$mi
dim <- mi["d"]
ev <- mi["ev"]
nointerp <- any(ev == c(3, 7, 8))
wh <- 1
n <- 1
if(is.null(newdata)) {
if(missing(where))
where <- if(nointerp) "fitp" else "grid"
if(where == "grid")
newdata <- lfmarg(object)
if(any(where == c("fitp", "ev", "fitpoints"))) {
where <- "fitp"
newdata <- lfknots(object, what = "x", delete.pv = FALSE)
}
if(where == "data")
newdata <- locfit.matrix(object)$x
if(where == "vect")
stop("you must give the vector points")
}
else {
where <- "vect"
if(is.data.frame(newdata))
newdata <- as.matrix(model.frame(delete.response(object$terms), newdata))
else if(is.list(newdata))
where <- "grid"
else newdata <- as.matrix(newdata)
}
if(is.null(tr)) {
if(what == "coef")
tr <- object$trans
else tr <- function(x)
x
}
if((nointerp) && (where == "grid") && (dim == 2)) {
nv <- object$nvc["nv"]
x <- object$eva$xev[2 * (1:nv) - 1]
y <- object$eva$xev[2 * (1:nv)]
z <- preplot.locfit.raw(object, 0, "fitp", what, band)$y
# haveAkima <- require(akima)
#if (! haveAkima) stop("The akima package is needed for the interp() function. Please note its no-compercial-use license.")
fhat <- interp::interp(x, y, z, newdata[[1]], newdata[[2]], ncp = 2)$z
}
else {
z <- preplot.locfit.raw(object, newdata, where, what, band)
fhat <- z$y
}
fhat[fhat == 0.1278433] <- NA
band <- pmatch(band, c("none", "global", "local", "prediction"))
if(band > 1)
sse <- z$se
else sse <- numeric(0)
if(where != "grid")
newdata <- list(xev = newdata, where = where)
else newdata$where <- where
data <- if(get.data) locfit.matrix(object) else list()
if((f3d) | (dim > 3))
dim <- 3
ret <- list(xev = newdata, fit = fhat, se.fit = sse, residual.scale = sqrt(
object$dp["rv"]), critval = object$critval, trans = tr, vnames = object$
vnames, yname = object$yname, dim = as.integer(dim), data = data)
class(ret) <- "preplot.locfit"
ret
}
"preplot.locfit.raw"<-
function(object, newdata, where, what, band, ...)
{
wh <- pmatch(where, c("vect", "grid", "data", "fitp"))
switch(wh,
{
mg <- n <- nrow(newdata)
xev <- newdata
}
,
{
xev <- unlist(newdata)
mg <- sapply(newdata, length)
n <- prod(mg)
}
,
{
mg <- n <- object$mi["n"]
xev <- newdata
}
,
{
mg <- n <- object$nvc["nv"]
xev <- newdata
}
)
.C("spreplot",
xev = as.numeric(object$eva$xev),
coef = as.numeric(object$eva$coef),
sv = as.numeric(object$cell$sv),
ce = as.integer(c(object$cell$ce, object$cell$s, object$cell$lo, object$
cell$hi)),
x = as.numeric(xev),
y = numeric(n),
se = numeric(n),
wpc = as.numeric(object$eva$pc),
scale = as.numeric(object$eva$scale),
m = as.integer(mg),
nvc = as.integer(object$nvc),
mi = as.integer(object$mi),
dp = as.numeric(object$dp),
mg = as.integer(object$eva$ev$mg),
deriv = as.integer(object$deriv),
nd = as.integer(length(object$deriv)),
sty = as.integer(object$sty),
wh = as.integer(wh),
what = c(what, band),
bs = list(eval(object$call$basis)), PACKAGE="locfit")
}
"print.preplot.locfit"<-
function(x, ...)
{
print(x$trans(x$fit))
invisible(x)
}
"plot.locfit.1d"<-
function(x, add=FALSE, main="", xlab="default", ylab=x$yname, type="l",
ylim, lty = 1, col = 1, ...) {
y <- x$fit
nos <- !is.na(y)
xev <- x$xev[[1]][nos]
y <- y[nos]
ord <- order(xev)
if(xlab == "default")
xlab <- x$vnames
tr <- x$trans
yy <- tr(y)
if(length(x$se.fit) > 0) {
crit <- x$critval$crit.val
cup <- tr((y + crit * x$se.fit))[ord]
clo <- tr((y - crit * x$se.fit))[ord]
}
ndat <- 0
if(length(x$data) > 0) {
ndat <- nrow(x$data$x)
xdsc <- rep(x$data$sc, length.out = ndat)
xdyy <- rep(x$data$y, length.out = ndat)
dok <- xdsc > 0
}
if(missing(ylim)) {
if(length(x$se.fit) > 0)
ylim <- c(min(clo), max(cup))
else ylim <- range(yy)
if(ndat > 0)
ylim <- range(c(ylim, xdyy[dok]/xdsc[dok]))
}
if(!add) {
plot(xev[ord], yy[ord], type = "n", xlab = xlab, ylab = ylab, main = main,
xlim = range(x$xev[[1]]), ylim = ylim, ...)
}
lines(xev[ord], yy[ord], type = type, lty = lty, col = col)
if(length(x$se.fit) > 0) {
lines(xev[ord], cup, lty = 2)
lines(xev[ord], clo, lty = 2)
}
if(ndat > 0) {
xd <- x$data$x[dok]
yd <- xdyy[dok]/xdsc[dok]
cd <- rep(x$data$ce, length.out = ndat)[dok]
if(length(x$data$y) < 2) {
rug(xd[cd == 0])
if(any(cd == 1))
rug(xd[cd == 1], ticksize = 0.015)
}
else {
plotbyfactor(xd, yd, cd, col = col, pch = c("o", "+"), add = TRUE)
}
}
invisible(NULL)
}
"plot.locfit.2d"<-
function(x, type="contour", main, xlab, ylab, zlab=x$yname, ...)
{
if(x$xev$where != "grid")
stop("Can only plot from grids")
if(missing(xlab))
xlab <- x$vnames[1]
if(missing(ylab))
ylab <- x$vnames[2]
tr <- x$trans
m1 <- x$xev[[1]]
m2 <- x$xev[[2]]
y <- matrix(tr(x$fit))
if(type == "contour")
contour(m1, m2, matrix(y, nrow = length(m1)), ...)
if(type == "image")
image(m1, m2, matrix(y, nrow = length(m1)), ...)
if((length(x$data) > 0) && any(type == c("contour", "image"))) {
xd <- x$data$x
ce <- rep(x$data$ce, length.out = nrow(xd))
points(xd[ce == 0, 1], xd[ce == 0, 2], pch = "o")
if(any(ce == 1))
points(xd[ce == 1, 1], xd[ce == 1, 2], pch = "+")
}
if(type == "persp") {
nos <- is.na(y)
y[nos] <- min(y[!nos])
persp(m1, m2, matrix(y, nrow = length(m1)), zlab=zlab, ...)
}
if(!missing(main))
title(main = main)
invisible(NULL)
}
"plot.locfit.3d"<-
function(x, main = "", pv, tv, type = "level", pred.lab = x$vnames, resp.lab =
x$yname, crit = 1.96, ...)
{
xev <- x$xev
if(xev$where != "grid")
stop("Can only plot from grids")
xev$where <- NULL
newx <- as.matrix(expand.grid(xev))
newy <- x$trans(x$fit)
wh <- rep("f", length(newy))
if(length(x$data) > 0) {
dat <- x$data
for(i in tv) {
m <- xev[[i]]
dat$x[, i] <- m[1 + round((dat$x[, i] - m[1])/(m[2] - m[1]))]
}
newx <- rbind(newx, dat$x)
if(is.null(dat$y))
newy <- c(newy, rep(NA, nrow(dat$x)))
else {
newy <- c(newy, dat$y/dat$sc)
newy[is.na(newy)] <- 0
}
wh <- c(wh, rep("d", nrow(dat$x)))
}
if(length(tv) == 0) {
newdat <- data.frame(newy, newx[, pv])
names(newdat) <- c("y", paste("pv", 1:length(pv), sep = ""))
}
else {
newdat <- data.frame(newx[, tv], newx[, pv], newy)
names(newdat) <- c(paste("tv", 1:length(tv), sep = ""), paste("pv", 1:
length(pv), sep = ""), "y")
for(i in 1:length(tv))
newdat[, i] <- as.factor(signif(newdat[, i], 5))
}
loc.strip <- function(...)
strip.default(..., strip.names = c(TRUE, TRUE), style = 1)
if(length(pv) == 1) {
clo <- cup <- numeric(0)
if(length(x$se.fit) > 0) {
if((!is.null(class(crit))) && (inherits(crit, "kappa")))
crit <- crit$crit.val
cup <- x$trans((x$fit + crit * x$se.fit))
clo <- x$trans((x$fit - crit * x$se.fit))
}
formula <- switch(1 + length(tv),
y ~ pv1,
y ~ pv1 | tv1,
y ~ pv1 | tv1 * tv2,
y ~ pv1 | tv1 * tv2 * tv3)
pl <- xyplot(formula, xlab = pred.lab[pv], ylab = resp.lab, main = main,
type = "l", cup = cup, wh = wh, panel = panel.xyplot.lf, data
= newdat, strip = loc.strip, ...)
}
if(length(pv) == 2) {
formula <- switch(1 + length(tv),
y ~ pv1 * pv2,
y ~ pv1 * pv2 | tv1,
y ~ pv1 * pv2 | tv1 * tv2,
y ~ pv1 * pv2 | tv1 * tv2 * tv3)
if(type == "contour")
pl <- contourplot(formula, xlab = pred.lab[pv[1]], ylab = pred.lab[pv[2]],
main = main, data = newdat, strip = loc.strip, ...)
if(type == "level")
pl <- levelplot(formula, xlab = pred.lab[pv[1]], ylab = pred.lab[pv[2]],
main = main, data = newdat, strip = loc.strip, ...)
if((type == "persp") | (type == "wireframe"))
pl <- wireframe(formula, xlab = pred.lab[pv[1]], ylab = pred.lab[pv[2]],
zlab = resp.lab, data = newdat, strip = loc.strip, ...)
}
if(length(tv) > 0) {
## if(exists("is.R") && is.function(is.R) && is.R())
names(pl$cond) <- pred.lab[tv]
## else names(attr(pl$glist, "endpts")) <- attr(pl$glist, "names") <- names(
## attr(pl$glist, "index")) <- pred.lab[tv]
}
pl
}
"panel.xyplot.lf"<-
function(x, y, subscripts, clo, cup, wh, type = "l", ...)
{
wh <- wh[subscripts]
panel.xyplot(x[wh == "f"], y[wh == "f"], type = type, ...)
if(length(clo) > 0) {
panel.xyplot(x[wh == "f"], clo[subscripts][wh == "f"], type = "l", lty = 2,
...)
panel.xyplot(x[wh == "f"], cup[subscripts][wh == "f"], type = "l", lty = 2,
...)
}
if(any(wh == "d")) {
yy <- y[wh == "d"]
if(any(is.na(yy)))
rug(x[wh == "d"])
else panel.xyplot(x[wh == "d"], yy)
}
}
"plot.preplot.locfit"<-
function(x, pv, tv, ...)
{
if(x$dim == 1)
plot.locfit.1d(x, ...)
if(x$dim == 2)
plot.locfit.2d(x, ...)
if(x$dim >= 3)
print(plot.locfit.3d(x, pv=pv, tv=tv, ...))
invisible(NULL)
}
"summary.preplot.locfit"<-
function(object, ...)
object$trans(object$fit)
## Deepayan Sarkar's patched version:
"panel.locfit"<-
function(x, y, subscripts, z, rot.mat, distance, shade,
light.source, xlim, ylim, zlim, xlim.scaled, ylim.scaled, zlim.scaled, region,
col, lty, lwd, alpha, col.groups, polynum, drape, at,
xlab, ylab, zlab, xlab.default, ylab.default, zlab.default, aspect, panel.aspect,
scales.3d, contour, labels, ...)
{
if(!missing(z)) {
zs <- z[subscripts]
fit <- locfit.raw(cbind(x, y), zs, ...)
marg <- lfmarg(fit, m = 10)
zp <- predict(fit, marg)
if(!missing(contour)) {
#print("contour")
#print(range(zp))
#lattice::render.contour.trellis(marg[[1]], marg[[2]], zp, at = at)
lattice::panel.contourplot(marg[[1]], marg[[2]], zp, 1:length(zp), at=at)
}
else {
# loc.dat <-
# cbind(as.matrix(expand.grid(x = marg[[1]],
# y = marg[[1]])),
# z = zp)
# lattice::render.3d.trellis(cbind(x = x, y = y, z = z[subscripts]),
# type = "cloud",
# xyz.labs = xyz.labs,
# xyz.axes = xyz.axes,
# xyz.mid = xyz.mid,
# xyz.minmax = xyz.minmax,
# xyz.range = xyz.range,
# col.regions = col.regions,
# at = at,
# drape = drape)
lattice::panel.wireframe(marg[[1]], marg[[2]], zp,
rot.mat, distance, shade,
light.source, xlim, ylim, zlim,
xlim.scaled, ylim.scaled, zlim.scaled,
col, lty, lwd, alpha, col.groups, polynum, drape, at)
}
}
else {
panel.xyplot(x, y, ...)
args <- list(x = x, y = y, ...)
ok <- names(formals(locfit.raw))
llines.locfit(do.call("locfit.raw",
args[ok[ok %in% names(args)]]))
}
}
llines.locfit <-
function (x, m = 100, tr = x$trans, ...)
{
newx <- lfmarg(x, m = m)[[1]]
y <- predict(x, newx, tr = tr)
llines(newx, y, ...)
}
## "panel.locfit"<-
# function(x, y, subscripts, z, xyz.labs, xyz.axes, xyz.mid, xyz.minmax,
# xyz.range, col.regions, at, drape, contour, region, groups, ...)
# {
# if(!missing(z)) {
# zs <- z[subscripts]
# fit <- locfit.raw(cbind(x, y), zs, ...)
# marg <- lfmarg(fit, m = 10)
# zp <- predict(fit, marg)
# if(!missing(contour)) {
# print("contour")
# print(range(zp))
# render.contour.trellis(marg[[1]], marg[[2]], zp, at = at)
# }
# else {
# loc.dat <- cbind(as.matrix(expand.grid(x = marg[[1]], y = marg[[1]])), z
# = zp)
# render.3d.trellis(cbind(x = x, y = y, z = z[subscripts]), type = "cloud",
# xyz.labs = xyz.labs, xyz.axes = xyz.axes, xyz.mid = xyz.mid, xyz.minmax
# = xyz.minmax, xyz.range = xyz.range, col.regions = col.regions, at =
# at, drape = drape)
# }
# }
# else {
# panel.xyplot(x, y)
# lines(locfit.raw(x, y, ...))
# }
# }
"lfmarg"<-
function(xlim, m = 40)
{
if(!is.numeric(xlim)) {
d <- xlim$mi["d"]
xlim <- xlim$box
}
else d <- length(m)
marg <- vector("list", d)
m <- rep(m, length.out = d)
for(i in 1:d)
marg[[i]] <- seq(xlim[i], xlim[i + d], length.out = m[i])
marg
}
"lfeval"<-
function(object)
object$eva
"plot.lfeval"<-
function(x, add = FALSE, txt = FALSE, ...)
{
if(inherits(x, "locfit"))
x <- x$eva
d <- length(x$scale)
v <- matrix(x$xev, nrow = d)
if(d == 1) {
xx <- v[1, ]
y <- x$coef[, 1]
}
if(d == 2) {
xx <- v[1, ]
y <- v[2, ]
}
if(!add) {
plot(xx, y, type = "n", ...)
}
points(xx, y, ...)
if(txt)
text(xx, y, (1:length(xx)) - 1)
invisible(x)
}
"print.lfeval"<-
function(x, ...)
{
if(inherits(x, "locfit"))
x <- x$eva
d <- length(x$scale)
ret <- matrix(x$xev, ncol = d, byrow = TRUE)
print(ret)
}
"lflim"<-
function(limits, nm, ret)
{
d <- length(nm)
if(is.numeric(limits))
ret <- limits
else {
z <- match(nm, names(limits))
for(i in 1:d)
if(!is.na(z[i])) ret[c(i, i + d)] <- limits[[z[i]]]
}
as.numeric(ret)
}
"plot.eval"<-
function(x, add = FALSE, text = FALSE, ...)
{
d <- x$mi["d"]
v <- matrix(x$eva$xev, nrow = d)
ev <- x$mi["ev"]
pv <- if(any(ev == c(1, 2))) as.logical(x$cell$s) else rep(FALSE, ncol(v))
if(!add) {
plot(v[1, ], v[2, ], type = "n", xlab = x$vnames[1], ylab = x$vnames[2])
}
if(text)
text(v[1, ], v[2, ], (1:x$nvc["nv"]) - 1)
else {
if(any(!pv))
points(v[1, !pv], v[2, !pv], ...)
if(any(pv))
points(v[1, pv], v[2, pv], pch = "*", ...)
}
if(any(x$mi["ev"] == c(1, 2))) {
zz <- .C("triterm",
as.numeric(v),
h = as.numeric(lfknots(x, what = "h", delete.pv = FALSE)),
as.integer(x$cell$ce),
lo = as.integer(x$cell$lo),
hi = as.integer(x$cell$hi),
as.numeric(x$eva$scale),
as.integer(x$nvc),
as.integer(x$mi),
as.numeric(x$dp),
nt = integer(1),
term = integer(600),
box = x$box, PACKAGE="locfit")
ce <- zz$term + 1
}
else ce <- x$cell$ce + 1
if(any(x$mi["ev"] == c(1, 5, 7))) {
vc <- 2^d
ce <- matrix(ce, nrow = vc)
segments(v[1, ce[1, ]], v[2, ce[1, ]], v[1, ce[2, ]], v[2, ce[2, ]],
...)
segments(v[1, ce[1, ]], v[2, ce[1, ]], v[1, ce[3, ]], v[2, ce[3, ]],
...)
segments(v[1, ce[2, ]], v[2, ce[2, ]], v[1, ce[4, ]], v[2, ce[4, ]],
...)
segments(v[1, ce[3, ]], v[2, ce[3, ]], v[1, ce[4, ]], v[2, ce[4, ]],
...)
}
if(any(x$mi["ev"] == c(2, 8))) {
vc <- d + 1
m <- matrix(ce, nrow = 3)
segments(v[1, m[1, ]], v[2, m[1, ]], v[1, m[2, ]], v[2, m[2, ]], ...)
segments(v[1, m[1, ]], v[2, m[1, ]], v[1, m[3, ]], v[2, m[3, ]], ...)
segments(v[1, m[2, ]], v[2, m[2, ]], v[1, m[3, ]], v[2, m[3, ]], ...)
}
invisible(NULL)
}
"rv"<-
function(fit)
fit$dp["rv"]
"rv<-"<-
function(fit, value)
{
fit$dp["rv"] <- value
fit
}
"regband"<-
function(formula, what = c("CP", "GCV", "GKK", "RSW"), deg = 1, ...)
{
m <- match.call()
m$geth <- 3
m$deg <- c(deg, 4)
m$what <- NULL
m$deriv <- match(what, c("CP", "GCV", "GKK", "RSW"))
m[[1]] <- as.name("locfit")
z <- eval(m, sys.frame(sys.parent()))
names(z) <- what
z[1:length(what)]
}
"kdeb"<-
function(x, h0 = 0.01 * sd, h1 = sd, meth = c("AIC", "LCV", "LSCV", "BCV",
"SJPI", "GKK"), kern = "gauss", gf = 2.5)
{
n <- length(x)
sd <- sqrt(var(x))
z <- .C("kdeb",
x = as.numeric(x),
mi = as.integer(n),
band = numeric(length(meth)),
ind = integer(n),
h0 = as.numeric(gf * h0),
h1 = as.numeric(gf * h1),
meth = as.integer(match(meth, c("AIC", "LCV", "LSCV", "BCV", "SJPI", "GKK")
)),
nmeth = as.integer(length(meth)),
kern = pmatch(kern, c("rect", "epan", "bisq", "tcub", "trwt", "gauss")),
PACKAGE="locfit")
band <- z$band
names(band) <- meth
band
}
"lfknots"<-
function(x, tr, what = c("x", "coef", "h", "nlx"), delete.pv = TRUE)
{
nv <- x$nvc["nv"]
d <- x$mi["d"]
p <- x$mi["p"]
z <- 0:(nv - 1)
ret <- matrix(0, nrow = nv, ncol = 1)
rname <- character(0)
if(missing(tr))
tr <- x$trans
coef <- x$eva$coef
for(wh in what) {
if(wh == "x") {
ret <- cbind(ret, matrix(x$eva$xev, ncol = d, byrow = TRUE))
rname <- c(rname, x$vnames)
}
if(wh == "coef") {
d0 <- coef[, 1]
d0[d0 == 0.1278433] <- NA
ret <- cbind(ret, tr(d0))
rname <- c(rname, "mu hat")
}
if(wh == "f1") {
ret <- cbind(ret, coef[, 1 + (1:d)])
rname <- c(rname, paste("d", 1:d, sep = ""))
}
if(wh == "nlx") {
ret <- cbind(ret, coef[, d + 2])
rname <- c(rname, "||l(x)||")
}
if(wh == "nlx1") {
ret <- cbind(ret, coef[, d + 2 + (1:d)])
rname <- c(rname, paste("nlx-d", 1:d, sep = ""))
}
if(wh == "se") {
ret <- cbind(ret, sqrt(x$dp["rv"]) * coef[, d + 2])
rname <- c(rname, "StdErr")
}
if(wh == "infl") {
z <- coef[, 2 * d + 3]
ret <- cbind(ret, z * z)
rname <- c(rname, "Influence")
}
if(wh == "infla") {
ret <- cbind(ret, coef[, 2 * d + 3 + (1:d)])
rname <- c(rname, paste("inf-d", 1:d, sep = ""))
}
if(wh == "lik") {
ret <- cbind(ret, coef[, 3 * d + 3 + (1:3)])
rname <- c(rname, c("LocLike", "fit.df", "res.df"))
}
if(wh == "h") {
ret <- cbind(ret, coef[, 3 * d + 7])
rname <- c(rname, "h")
}
if(wh == "deg") {
ret <- cbind(ret, coef[, 3 * d + 8])
rname <- c(rname, "deg")
}
}
ret <- as.matrix(ret[, -1])
if(nv == 1)
ret <- t(ret)
dimnames(ret) <- list(NULL, rname)
if((delete.pv) && (any(x$mi["ev"] == c(1, 2))))
ret <- ret[!as.logical(x$cell$s), ]
ret
}
"locfit.matrix"<-
function(fit, data)
{
m <- fit$call
n <- fit$mi["n"]
y <- ce <- base <- 0
w <- 1
if(m[[1]] == "locfit.raw") {
x <- as.matrix(eval(m$x, fit$frame))
if(!is.null(m$y))
y <- eval(m$y, fit$frame)
if(!is.null(m$weights))
w <- eval(m$weights, fit$frame)
if(!is.null(m$cens))
ce <- eval(m$cens, fit$frame)
if(!is.null(m$base))
base <- eval(m$base, fit$frame)
}
else {
Terms <- terms(as.formula(m$formula))
attr(Terms, "intercept") <- 0
m[[1]] <- as.name("model.frame")
z <- pmatch(names(m), c("formula", "data", "weights", "cens", "base",
"subset"))
for(i in length(z):2)
if(is.na(z[i])) m[[i]] <- NULL
frm <- eval(m, fit$frame)
vnames <- as.character(attributes(Terms)$variables)[-1]
if(attr(Terms, "response")) {
y <- model.extract(frm, "response")
vnames <- vnames[-1]
}
x <- as.matrix(frm[, vnames])
if(any(names(m) == "weights"))
w <- model.extract(frm, weights)
if(any(names(m) == "cens"))
ce <- model.extract(frm, "cens")
if(any(names(m) == "base"))
base <- model.extract(frm, base)
}
sc <- if(any((fit$mi["tg"] %% 64) == c(5:8, 11, 12))) w else 1
list(x = x, y = y, w = w, sc = sc, ce = ce, base = base)
}
"expit"<-
function(x)
{
y <- x
ix <- (x < 0)
y[ix] <- exp(x[ix])/(1 + exp(x[ix]))
y[!ix] <- 1/(1 + exp( - x[!ix]))
y
}
"plotbyfactor"<-
function(x, y, f, data, col = 1:10, pch = "O", add = FALSE, lg, xlab = deparse(
substitute(x)), ylab = deparse(substitute(y)), log = "", ...)
{
if(!missing(data)) {
x <- eval(substitute(x), data)
y <- eval(substitute(y), data)
f <- eval(substitute(f), data)
}
f <- as.factor(f)
if(!add)
plot(x, y, type = "n", xlab = xlab, ylab = ylab, log = log, ...)
lv <- levels(f)
col <- rep(col, length.out = length(lv))
pch <- rep(pch, length.out = length(lv))
for(i in 1:length(lv)) {
ss <- f == lv[i]
if(any(ss))
points(x[ss], y[ss], col = col[i], pch = pch[i])
}
if(!missing(lg))
legend(lg[1], lg[2], legend = levels(f), col = col, pch = paste(pch,
collapse = ""))
}
"hatmatrix"<-
function(formula, dc = TRUE, ...)
{
m <- match.call()
m$geth <- 1
m[[1]] <- as.name("locfit")
z <- eval(m, sys.frame(sys.parent()))
nvc <- z[[2]]
nvm <- nvc[1]
nv <- nvc[4]
matrix(z[[1]], ncol = nvm)[, 1:nv]
}
"locfit.robust"<-
function(x, y, weights, ..., iter = 3)
{
m <- match.call()
if((!is.numeric(x)) && (inherits(x, "formula"))) {
m1 <- m[[1]]
m[[1]] <- as.name("locfit")
m$lfproc <- m1
names(m)[[2]] <- "formula"
return(eval(m, sys.frame(sys.parent())))
}
n <- length(y)
lfr.wt <- rep(1, n)
m[[1]] <- as.name("locfit.raw")
for(i in 0:iter) {
m$weights <- lfr.wt
fit <- eval(m, sys.frame(sys.parent()))
res <- residuals(fit, type = "raw")
s <- median(abs(res))
lfr.wt <- pmax(1 - (res/(6 * s))^2, 0)^2
}
fit
}
"locfit.censor"<-
function(x, y, cens, ..., iter = 3, km = FALSE)
{
m <- match.call()
if((!is.numeric(x)) && (inherits(x, "formula"))) {
m1 <- m[[1]]
m[[1]] <- as.name("locfit")
m$lfproc <- m1
names(m)[[2]] <- "formula"
return(eval(m, sys.frame(sys.parent())))
}
lfc.y <- y
cens <- as.logical(cens)
m$cens <- m$iter <- m$km <- NULL
m[[1]] <- as.name("locfit.raw")
for (i in 0:iter) {
m$y <- lfc.y
fit <- eval(m, sys.frame(sys.parent()))
fh <- fitted(fit)
if(km) {
sr <- y - fh
lfc.y <- y + km.mrl(sr, cens)
}
else {
rdf <- sum(1 - cens) - 2 * fit$dp["df1"] + fit$dp["df2"]
sigma <- sqrt(sum((y - fh) * (lfc.y - fh))/rdf)
sr <- (y - fh)/sigma
lfc.y <- fh + (sigma * dnorm(sr))/pnorm( - sr)
}
lfc.y[!cens] <- y[!cens]
}
m$cens <- substitute(cens)
m$y <- substitute(y)
fit$call <- m
fit
}
"km.mrl"<-
function(times, cens)
{
n <- length(times)
if(length(cens) != length(times))
stop("times and cens must have equal length")
ord <- order(times)
times <- times[ord]
cens <- cens[ord]
n.alive <- n:1
haz.km <- (1 - cens)/n.alive
surv.km <- exp(cumsum(log(1 - haz.km[ - n])))
int.surv <- c(diff(times) * surv.km)
mrl.km <- c(rev(cumsum(rev(int.surv)))/surv.km, 0)
mrl.km[!cens] <- 0
mrl.km.ord <- numeric(n)
mrl.km.ord[ord] <- mrl.km
mrl.km.ord
}
"locfit.quasi"<-
function(x, y, weights, ..., iter = 3, var = abs)
{
m <- match.call()
if((!is.numeric(x)) && (inherits(x, "formula"))) {
m1 <- m[[1]]
m[[1]] <- as.name("locfit")
m$lfproc <- m1
names(m)[[2]] <- "formula"
return(eval(m, sys.frame(sys.parent())))
}
n <- length(y)
w0 <- lfq.wt <- if(missing(weights)) rep(1, n) else weights
m[[1]] <- as.name("locfit.raw")
for(i in 0:iter) {
m$weights <- lfq.wt
fit <- eval(m, sys.frame(sys.parent()))
fh <- fitted(fit)
lfq.wt <- w0/var(fh)
}
fit
}
"density.lf"<-
function(x, n=50, window="gaussian", width, from, to, cut=if(iwindow == 4)
0.75 else 0.5, ev=lfgrid(mg=n, ll=from, ur=to), deg=0,
family="density", link="ident", ...)
{
if(!exists("logb"))
logb <- log
# for R
x <- sort(x)
r <- range(x)
iwindow <- pmatch(window, c("rectangular", "triangular", "cosine", "gaussian"
), -1.)
if(iwindow < 0.)
kern <- window
else kern <- c("rect", "tria", NA, "gauss")[iwindow]
if(missing(width)) {
nbar <- logb(length(x), base = 2.) + 1.
width <- diff(r)/nbar * 0.5
}
if(missing(from))
from <- r[1.] - width * cut
if(missing(to))
to <- r[2.] + width * cut
if(to <= from)
stop("Invalid from/to values")
h <- width/2
if(kern == "gauss")
h <- h * 1.25
fit <- locfit.raw(lp(x, h = h, deg = deg), ev = ev, kern = kern, link = link,
family = family, ...)
list(x = fit$eva$xev, y = fit$eva$coef[, 1])
}
"smooth.lf"<-
function(x, y, xev = x, direct = FALSE, ...)
{
# just a simple smooth with (x,y) input, mu-hat output.
# locfit.raw options are valid.
if(missing(y)) {
y <- x
x <- 1:length(y)
}
if(direct) {
fit <- locfit.raw(x, y, ev = xev, geth = 7, ...)
fv <- fit$y
xev <- fit$x
if(is.matrix(x))
xev <- matrix(xev, ncol = ncol(x), byrow = TRUE)
}
else {
fit <- locfit.raw(x, y, ...)
fv <- predict(fit, xev)
}
list(x = xev, y = fv, call = match.call())
}
"gcv"<-
function(x, ...)
{
m <- match.call()
if(is.numeric(x))
m[[1]] <- as.name("locfit.raw")
else {
m[[1]] <- as.name("locfit")
names(m)[2] <- "formula"
}
fit <- eval(m, sys.frame(sys.parent()))
z <- fit$dp[c("lk", "df1", "df2")]
n <- fit$mi["n"]
z <- c(z, (-2 * n * z[1])/(n - z[2])^2)
names(z) <- c("lik", "infl", "vari", "gcv")
z
}
"gcvplot"<-
function(..., alpha, df = 2)
{
m <- match.call()
m[[1]] <- as.name("gcv")
m$df <- NULL
if(!is.matrix(alpha))
alpha <- matrix(alpha, ncol = 1)
k <- nrow(alpha)
z <- matrix(nrow = k, ncol = 4)
for(i in 1:k) {
m$alpha <- alpha[i, ]
z[i, ] <- eval(m, sys.frame(sys.parent()))
}
ret <- list(alpha = alpha, cri = "GCV", df = z[, df], values = z[, 4])
class(ret) <- "gcvplot"
ret
}
"plot.gcvplot"<-
function(x, xlab = "Fitted DF", ylab = x$cri, ...)
{
plot(x$df, x$values, xlab = xlab, ylab = ylab, ...)
}
"print.gcvplot"<-
function(x, ...)
plot.gcvplot(x = x, ...)
"summary.gcvplot"<-
function(object, ...)
{
z <- cbind(object$df, object$values)
dimnames(z) <- list(NULL, c("df", object$cri))
z
}
"aic"<-
function(x, ..., pen = 2)
{
m <- match.call()
if(is.numeric(x))
m[[1]] <- as.name("locfit.raw")
else {
m[[1]] <- as.name("locfit")
names(m)[2] <- "formula"
}
m$pen <- NULL
fit <- eval(m, sys.frame(sys.parent()))
dp <- fit$dp
z <- dp[c("lk", "df1", "df2")]
z <- c(z, -2 * z[1] + pen * z[2])
names(z) <- c("lik", "infl", "vari", "aic")
z
}
"aicplot"<-
function(..., alpha)
{
m <- match.call()
m[[1]] <- as.name("aic")
if(!is.matrix(alpha))
alpha <- matrix(alpha, ncol = 1)
k <- nrow(alpha)
z <- matrix(nrow = k, ncol = 4)
for(i in 1:k) {
m$alpha <- alpha[i, ]
z[i, ] <- eval(m, sys.frame(sys.parent()))
}
ret <- list(alpha = alpha, cri = "AIC", df = z[, 2], values = z[, 4])
class(ret) <- "gcvplot"
ret
}
"cp"<-
function(x, ..., sig2 = 1)
{
m <- match.call()
if(is.numeric(x))
m[[1]] <- as.name("locfit.raw")
else {
m[[1]] <- as.name("locfit")
names(m)[2] <- "formula"
}
m$sig2 <- NULL
fit <- eval(m, sys.frame(sys.parent()))
z <- c(fit$dp[c("lk", "df1", "df2")], fit$mi["n"])
z <- c(z, (-2 * z[1])/sig2 - z[4] + 2 * z[2])
names(z) <- c("lik", "infl", "vari", "n", "cp")
z
}
"cpplot"<-
function(..., alpha, sig2)
{
m <- match.call()
m[[1]] <- as.name("cp")
m$sig2 <- NULL
if(!is.matrix(alpha))
alpha <- matrix(alpha, ncol = 1)
k <- nrow(alpha)
z <- matrix(nrow = k, ncol = 5)
for(i in 1:k) {
m$alpha <- alpha[i, ]
z[i, ] <- eval(m, sys.frame(sys.parent()))
}
if(missing(sig2)) {
s <- (1:k)[z[, 3] == max(z[, 3])][1]
sig2 <- (-2 * z[s, 1])/(z[s, 4] - 2 * z[s, 2] + z[s, 3])
}
ret <- list(alpha = alpha, cri = "CP", df = z[, 3], values = (-2 * z[, 1])/
sig2 - z[, 4] + 2 * z[, 2])
class(ret) <- "gcvplot"
ret
}
"lcv"<-
function(x, ...)
{
m <- match.call()
if(is.numeric(x))
m[[1]] <- as.name("locfit.raw")
else {
m[[1]] <- as.name("locfit")
names(m)[2] <- "formula"
}
fit <- eval(m, sys.frame(sys.parent()))
z <- fit$dp[c("lk", "df1", "df2")]
res <- residuals(fit, type = "d2", cv = TRUE)
z <- c(z, sum(res))
names(z) <- c("lik", "infl", "vari", "cv")
z
}
"lcvplot"<-
function(..., alpha)
{
m <- match.call()
m[[1]] <- as.name("lcv")
if(!is.matrix(alpha))
alpha <- matrix(alpha, ncol = 1)
k <- nrow(alpha)
z <- matrix(nrow = k, ncol = 4)
for(i in 1:k) {
m$alpha <- alpha[i, ]
z[i, ] <- eval(m, sys.frame(sys.parent()))
}
ret <- list(alpha = alpha, cri = "LCV", df = z[, 2], values = z[, 4])
class(ret) <- "gcvplot"
ret
}
"lscv"<-
function(x, ..., exact = FALSE)
{
if(exact) {
ret <- lscv.exact(x, ...)
}
else {
m <- match.call()
m$exact <- NULL
if(is.numeric(x))
m[[1]] <- as.name("locfit.raw")
else {
m[[1]] <- as.name("locfit")
names(m)[2] <- "formula"
}
m$geth <- 6
ret <- eval(m, sys.frame(sys.parent()))
}
ret
}
"lscv.exact"<-
function(x, h = 0)
{
if(!is.null(attr(x, "alpha")))
h <- attr(x, "alpha")[2]
if(h <= 0)
stop("lscv.exact: h must be positive.")
ret <- .C("slscv",
x = as.numeric(x),
n = as.integer(length(x)),
h = as.numeric(h),
ret = numeric(2), PACKAGE="locfit")$ret
ret
}
"lscvplot"<-
function(..., alpha)
{
m <- match.call()
m[[1]] <- as.name("lscv")
if(!is.matrix(alpha))
alpha <- matrix(alpha, ncol = 1)
k <- nrow(alpha)
z <- matrix(nrow = k, ncol = 2)
for(i in 1:k) {
m$alpha <- alpha[i, ]
z[i, ] <- eval(m, sys.frame(sys.parent()))
}
ret <- list(alpha = alpha, cri = "LSCV", df = z[, 2], values = z[, 1])
class(ret) <- "gcvplot"
ret
}
"sjpi"<-
function(x, a)
{
dnorms <- function(x, k)
{
if(k == 0)
return(dnorm(x))
if(k == 1)
return( - x * dnorm(x))
if(k == 2)
return((x * x - 1) * dnorm(x))
if(k == 3)
return(x * (3 - x * x) * dnorm(x))
if(k == 4)
return((3 - x * x * (6 - x * x)) * dnorm(x))
if(k == 6)
return((-15 + x * x * (45 - x * x * (15 - x * x))) * dnorm(x))
stop("k too large in dnorms")
}
alpha <- a * sqrt(2)
n <- length(x)
M <- outer(x, x, "-")
s <- numeric(length(alpha))
for(i in 1:length(alpha)) {
s[i] <- sum(dnorms(M/alpha[i], 4))
}
s <- s/(n * (n - 1) * alpha^5)
h <- (s * 2 * sqrt(pi) * n)^(-0.2)
lambda <- diff(summary(x)[c(2, 5)])
A <- 0.92 * lambda * n^(-1/7)
B <- 0.912 * lambda * n^(-1/9)
tb <- - sum(dnorms(M/B, 6))/(n * (n - 1) * B^7)
sa <- sum(dnorms(M/A, 4))/(n * (n - 1) * A^5)
ah <- 1.357 * (sa/tb * h^5)^(1/7)
cbind(h, a, ah/sqrt(2), s)
}
"scb"<-
function(x, ..., ev = lfgrid(20), simul = TRUE, type = 1)
{
oc <- m <- match.call()
if(is.numeric(x))
m[[1]] <- as.name("locfit.raw")
else {
m[[1]] <- as.name("locfit")
names(m)[2] <- "formula"
}
m$type <- m$simul <- NULL
m$geth <- 70 + type + 10 * simul
m$ev <- substitute(ev)
fit <- eval(m, sys.frame(sys.parent()))
fit$call <- oc
class(fit) <- "scb"
fit
}
"plot.scb"<-
function(x, add = FALSE, ...)
{
fit <- x$trans(x$coef)
lower <- x$trans(x$lower)
upper <- x$trans(x$upper)
d <- x$d
if(d == 1)
plot.scb.1d(x, fit, lower, upper, add, ...)
if(d == 2)
plot.scb.2d(x, fit = fit, lower = lower, upper = upper, ...)
if(!any(d == c(1, 2)))
stop("Can't plot this scb")
}
"plot.scb.1d"<-
function(x, fit, lower, upper, add = FALSE, style = "band", ...)
{
if(style == "test") {
lower <- lower - fit
upper <- upper - fit
}
if(!add) {
yl <- range(c(lower, fit, upper))
plot(x$xev, fit, type = "l", ylim = yl, xlab = x$vnames[1])
}
lines(x$xev, lower, lty = 2)
lines(x$xev, upper, lty = 2)
if(is.null(x$call$deriv)) {
dx <- x$data$x
sc <- if(any((x$mi["tg"] %% 64) == c(5:8, 11, 12))) x$data$w else 1
dy <- x$data$y/sc
points(dx, dy)
}
if(style == "test")
abline(h = 0, lty = 3)
}
"plot.scb.2d" <- function(x, fit, lower, upper, style = "tl", ylim, ...) {
plot.tl <- function(x, y, z, nint = c(16, 15), v1, v2,
xlab=deparse(substitute(x)),
ylab=deparse(substitute(y)),
legend=FALSE, pch="", ...) {
xl <- range(x)
if (legend) {
mar <- par()$mar
if (mar[4] < 6.1)
par(mar = c(mar[1:3], 6.1))
on.exit(par(mar = mar))
dlt <- diff(xl)
xl[2] <- xl[2] + 0.02 * dlt
}
plot(1, 1, type = "n", xlim = xl, ylim = range(y), xlab = xlab,
ylab = ylab, ...)
nx <- length(x)
ny <- length(y)
if (missing(v)) {
v <- seq(min(z) - 0.0001, max(z), length.out = nint + 1)
} else {
nint <- length(v) - 1
}
ix <- rep(1:nx, ny)
iy <- rep(1:ny, rep(nx, ny))
r1 <- range(z[, 1])
r2 <- range(z[, 2])
hue <- if (missing(v1)) {
floor((nint[1] * (z[, 1] - r1[1]))/(r1[2] - r1[1]) * 0.999999999)
} else cut(z[, 1], v1) - 1
sat <- if (missing(v2)) {
floor((nint[2] * (z[, 2] - r2[1]))/(r2[2] - r2[1]) * 0.999999999)
} else cut(z[, 2], v2) - 1
col <- hue + nint[1] * sat + 1
x <- c(2 * x[1] - x[2], x, 2 * x[nx] - x[nx - 1])
y <- c(2 * y[1] - y[2], y, 2 * y[ny] - y[ny - 1])
x <- (x[1:(nx + 1)] + x[2:(nx + 2)])/2
y <- (y[1:(ny + 1)] + y[2:(ny + 2)])/2
for (i in unique(col)) {
u <- col == i
if(pch == "") {
xx <- rbind(x[ix[u]], x[ix[u] + 1], x[ix[u] + 1], x[ix[u]], NA)
yy <- rbind(y[iy[u]], y[iy[u]], y[iy[u] + 1], y[iy[u] + 1], NA)
polygon(xx, yy, col = i, border = 0)
}
else points(x[ix[u]], y[iy[u]], col = i, pch = pch)
}
if(legend) {
yv <- seq(min(y), max(y), length = length(v))
x1 <- max(x) + 0.02 * dlt
x2 <- max(x) + 0.06 * dlt
for(i in 1:nint) {
polygon(c(x1, x2, x2, x1), rep(yv[i:(i + 1)], c(2, 2)),
col = i, border = 0)
}
axis(side = 4, at = yv, labels = v, adj = 0)
}
}
if(style == "trell") {
if(missing(ylim))
ylim <- range(c(fit, lower, upper))
loc.dat = data.frame(x1 = x$xev[, 1], x2 = x$xev[, 2], y = fit)
pl <- xyplot(y ~ x1 | as.factor(x2), data = loc.dat,
panel = panel.xyplot.lf, clo=lower, cup=upper,
wh=rep("f", nrow(loc.dat)))
plot(pl)
}
if(style == "tl") {
ux <- unique(x$xev[, 1])
uy <- unique(x$xev[, 2])
sig <- abs(x$coef/x$sd)
rv1 <- max(abs(fit)) * 1.0001
v1 <- seq( - rv1, rv1, length.out = 17)
v2 <- - c(-1e-100, crit(const = x$kap, cov = c(0.5, 0.7, 0.8, 0.85,
0.9, 0.95, 0.98, 0.99, 0.995,
0.999, 0.9999))$crit.val,
1e+300)
plot.tl(ux, uy, cbind(fit, - sig), v1 = v1, v2 = v2,
xlab = x$vnames[1], ylab = x$vnames[2])
}
}
"print.scb"<-
function(x, ...)
{
m <- cbind(x$xev, x$trans(x$coef), x$trans(x$lower), x$trans(x$upper))
dimnames(m) <- list(NULL, c(x$vnames, "fit", "lower", "upper"))
print(m)
}
"kappa0"<-
function(formula, cov=0.95, ev=lfgrid(20), ...)
{
if(inherits(formula, "locfit")) {
m <- formula$call
}
else {
m <- match.call()
m$cov <- NULL
}
m$dc <- TRUE
m$geth <- 2
m$ev <- substitute(ev)
m[[1]] <- as.name("locfit")
z <- eval(m, sys.frame(sys.parent()))
crit(const = z$const, d = z$d, cov = cov)
}
"crit"<-
function(fit, const = c(0, 1), d = 1, cov = 0.95, rdf = 0)
{
if(!missing(fit)) {
z <- fit$critval
if(missing(const) & missing(d) & missing(cov))
return(z)
if(!missing(const))
z$const <- const
if(!missing(d))
z$d <- d
if(!missing(cov))
z$cov <- cov
if(!missing(rdf))
z$rdf <- rdf
}
else {
z <- list(const = const, d = d, cov = cov, rdf = rdf, crit.val = 0)
class(z) <- "kappa"
}
z$crit.val <- .C("scritval",
k0 = as.numeric(z$const),
d = as.integer(z$d),
cov = as.numeric(z$cov),
m = as.integer(length(z$const)),
rdf = as.numeric(z$rdf),
x = numeric(1),
k = as.integer(1), PACKAGE="locfit")$x
z
}
"crit<-"<-
function(fit, value)
{
if(is.numeric(value))
fit$critval$crit.val <- value[1]
else {
if(!inherits(value, "kappa"))
stop("crit<-: value must be numeric or class kappa")
fit$critval <- value
}
fit
}
"spence.15"<-
function(y)
{
n <- length(y)
y <- c(rep(y[1], 7), y, rep(y[n], 7))
n <- length(y)
k <- 3:(n - 2)
a3 <- y[k - 1] + y[k] + y[k + 1]
a2 <- y[k - 2] + y[k + 2]
y1 <- y[k] + 3 * (a3 - a2)
n <- length(y1)
k <- 1:(n - 3)
y2 <- y1[k] + y1[k + 1] + y1[k + 2] + y1[k + 3]
n <- length(y2)
k <- 1:(n - 3)
y3 <- y2[k] + y2[k + 1] + y2[k + 2] + y2[k + 3]
n <- length(y3)
k <- 1:(n - 4)
y4 <- y3[k] + y3[k + 1] + y3[k + 2] + y3[k + 3] + y3[k + 4]
y4/320
}
"spence.21"<-
function(y)
{
n <- length(y)
y <- c(rep(y[1], 10), y, rep(y[n], 10))
n <- length(y)
k <- 4:(n - 3)
y1 <- - y[k - 3] + y[k - 1] + 2 * y[k] + y[k + 1] - y[k + 3]
n <- length(y1)
k <- 4:(n - 3)
y2 <- y1[k - 3] + y1[k - 2] + y1[k - 1] + y1[k] + y1[k + 1] + y1[k + 2] + y1[
k + 3]
n <- length(y2)
k <- 3:(n - 2)
y3 <- y2[k - 2] + y2[k - 1] + y2[k] + y2[k + 1] + y2[k + 2]
n <- length(y3)
k <- 3:(n - 2)
y4 <- y3[k - 2] + y3[k - 1] + y3[k] + y3[k + 1] + y3[k + 2]
y4/350
}
"store"<-
function(data = FALSE, grand = FALSE)
{
lfmod <- c("ang", "gam.lf", "gam.slist", "lf", "left", "right", #"lfbas",
"cpar", "lp")
lfmeth <- c("fitted.locfit", "formula.locfit", "predict.locfit",
"lines.locfit", "points.locfit", "print.locfit", "residuals.locfit",
"summary.locfit", "print.summary.locfit")
lfev <- c("rbox", "gr", "dat", "xbar", "none")
lfplo <- c("plot.locfit", "preplot.locfit", "preplot.locfit.raw",
"print.preplot.locfit", "plot.locfit.1d", "plot.locfit.2d",
"plot.locfit.3d", "panel.xyplot.lf", "plot.preplot.locfit",
"summary.preplot.locfit", "panel.locfit", "lfmarg")
lffre <- c("hatmatrix", "locfit.robust", "locfit.censor", "km.mrl",
"locfit.quasi", "density.lf", "smooth.lf")
lfscb <- c("scb", "plot.scb", "plot.scb.1d", "plot.scb.2d", "print.scb",
"kappa0", "crit", "crit<-", "plot.tl")
lfgcv <- c("gcv", "gcvplot", "plot.gcvplot", "print.gcvplot",
"summary.gcvplot", "aic", "aicplot", "cp", "cpplot", "lcv", "lcvplot",
"lscv", "lscv.exact", "lscvplot", "sjpi")
lfspen <- c("spence.15", "spence.21")
lffuns <- c("locfit", "locfit.raw", lfmod, lfmeth, lfev, lfplo, "lfeval",
"plot.lfeval", "print.lfeval", "lflim", "plot.eval", "rv", "rv<-",
"regband", "kdeb", "lfknots", "locfit.matrix", "expit", "plotbyfactor",
lffre, lfgcv, lfscb, lfspen, "store")
lfdata <- c("bad", "cltest", "cltrain", "co2", "diab", "geyser", "ethanol",
"mcyc", "morths", "border", "heart", "trimod", "insect", "iris", "spencer",
"stamp")
lfgrand <- c("locfit.raw", "crit", "predict.locfit", "preplot.locfit",
"preplot.locfit.raw", "expit", "rv", "rv<-", "knots") #"lfbas"
dump(lffuns, "S/locfit.s")
if(data)
dump(lfdata, "S/locfit.dat")
if(grand)
dump(lfgrand, "src-gr/lfgrand.s")
dump(lffuns, "R/locfit.s")
}
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