Nothing
R/wp.R
In gamlss: Generalised Additive Models for Location Scale and Shape
#------------------------------------------------------------------------------------------
# Mikis Stasinopoulos
# last 10 - 5 - 13
#TO DO the weights with frequency i.e w=1,4,1,4,2,6
# is not implemented properly
# the idea here is to allow more that one variable in xvar
# this is achieved by using a formula specification for example ~Fl*A
# TO DO
# i) n.inter : what hapent in this case this is OK
# ii) xcut.points : OK it needs to use the argument
# iii) overlap : it seems is working
# iv) factor in xvar : OK
# also by increasing in the panel function lwd=.5 from lwd=.01 the plots are also shown in all versions rather than x11()
# This is a new version witch can take any object with resid()
# or the actual residuals using the argument resid
## worm plots based on the worm plot function in S-plus by Van Buuren and
## Fredriks (2001) Worm plot: a simple diagnostic device for modelling
## growth reference curves, Statist. Med.
## original created by Mikis Stasinopoulos and Bob Rigby, Friday, November 8, 2002.
## last change Tuersday
wp <- function ( object = NULL,
xvar = NULL,
resid = NULL,
n.inter = 4,
xcut.points = NULL,
overlap = 0,
xlim.all = 4,
xlim.worm = 3.5,
show.given = TRUE,
line = TRUE,
ylim.all = 12*sqrt(1/length(resid)),
ylim.worm = 12*sqrt(n.inter/length(resid)),
cex = 1,
cex.lab = 1,
pch = 21,
bg = "wheat",
col = "red",
bar.bg = c(num="light blue"),
...)
{
##-----------------------------------------------------------------------------
#------------------------------------------------------------------------------
# local functions
# i) panel.fun
# ii) check.overlap
# iii) get.intervals
#-----------------------------------------------------------------------------
panel.fun <- function (x, y, col = par("col"), bg = NA, pch = par("pch"),
cex = par("cex"), col.smooth = "red", span = 2/3, iter = 3, ...)
{
qq <- as.data.frame(qqnorm(y, plot = FALSE))
if(any(is.infinite(qq$y))) line <-FALSE # added 30-4-13 DS if any y Inf do not fit lm
qq$y <- qq$y - qq$x
grid(nx=NA,ny=NA, lwd = 2) # grid only in y-direction
# points(qq$x, qq$y, pch = 1, col = col, bg = bg, cex = 0.7)
points(qq$x, qq$y, pch = pch, col = col, bg = bg, cex = cex)
abline(0, 0, lty = 2, col = col)
abline(0, 100000, lty = 2, col = col)
yuplim <- 10*sqrt(1/length(qq$y))
level <- .95
lz <- -xlim.worm
# lz <- -2.75
hz <- xlim.worm
# hz <- 2.75
dz <- 0.25
z <- seq(lz,hz,dz)
p <- pnorm(z)
se <- (1/dnorm(z))*(sqrt(p*(1-p)/length(qq$y)))
low <- qnorm((1-level)/2)*se
high <- -low
# if ( any(abs(qq$y)>ylim.worm) )
{
no.points <- length(qq$y)
total.points <<- total.points+no.points
no.mis <- sum(abs(qq$y)>ylim.worm)
cat("number of missing points from plot=", no.mis," out of ",no.points,"\n")
if ( any(abs(qq$y)>ylim.worm) ) warning("Some points are missed out ", "\n","increase the y limits using ylim.worm" )
}
if ( any(abs(qq$x)>xlim.worm) )
{
warning("Some points are missed out ", "\n","increase the x limits using xlim.worm" )
}
# se <- (1/dnorm(z))*(sqrt(p*(1-p)*n.inter/length(xvar)))
# low <- qnorm((1-level)/2)*se
# high <- -low
lines(z, low, lty=2, lwd=.5)
lines(z, high, lty=2, lwd=.5)
if(line == TRUE)
{
fit <- lm(y ~ x+I(x^2)+I(x^3), data=qq) #poly(qq$x,3))
s <- spline(qq$x, fitted(fit))
flags <- s$x > -2.5 & s$x < 2.5
lines(list(x = s$x[flags], y = s$y[flags]), col=col, lwd=.5)
assign("coef1",coef(fit),envir = parent.frame(n=3))
assign("coef" , c(coef, coef1),envir = parent.frame(n=3))
}
}
##-----------------------------------------------------------------------------
check.overlap <- function(interval)
{
if (!is.matrix(interval) ) {stop(paste("The interval specified is not a matrix."))}
if (dim(interval)[2] !=2) {stop(paste("The interval specified is not a valid matrix.\nThe number of columns should be equal to 2."))}
crows = dim(interval)[1]
for (i in 1:(crows-1))
{
#if (interval[i,2] != interval[i+1,1]) {interval[i+1,1]=interval[i,2]}
if (!(abs(interval[i,2]-interval[i+1,1])<0.0001)) {interval[i+1,1]=interval[i,2]}
}
return(interval)
}
##-----------------------------------------------------------------------------=
# the problem here is that coplot uses for given.values MS Tuesday, September 21, 2004
# min <= x <= 20 min <= x < 20 min <= x <= 20-extra
# 20 <= x <= 30 instead of 20 <= x < 30 here uses 20 <= x <= 30-extra
# 30 <= x <= max 30 <= x <= max 30 <= x <= max+extra
get.intervals <- function (xvar, xcut.points )
{
if (!is.vector(xcut.points)) {stop(paste("The interval is not a vector."))}
if ( any((xcut.points < min(xvar)) | any(xcut.points > max(xvar))))
{stop(paste("The specified `xcut.points' are not within the range of the x: (", min(xvar),
" , ", max(xvar), ")"))}
extra <- (max(xvar)-min(xvar))/100000
int <- c(min(xvar), xcut.points, (max(xvar)+2*extra))
ii <- 1:(length(int)-1)
r <- 2:length(int)
x1 <- int[ii]
xr <- int[r]-extra
if (any(x1>xr)) {stop(paste("The interval is are not in a increasing order."))}
cbind(x1,xr)
}
##------------------------------------------------------------------------------
# this function comes from coplot() to help to get the variables used if more that one xvar is used
deparen <- function(expr)
{
while (is.language(expr) && !is.name(expr) && deparse(expr[[1L]])[1L] ==
"(") expr <- expr[[2L]]
expr
}
##------------------------------------------------------------------------------
##-here is the main function ---------------------------------------------------
#-------------------------------------------------------------------------------
## get residuals
if (is.null(object)&&is.null(resid)) stop(paste("A fitted object with resid() method or the argument resid should be used ", "\n", ""))
resid <- if (is.null(object)) resid else resid(object)
DataExist <- FALSE
## get data if exist
#if (is.null(data))
# {
if (!is.null(object)&&any(grepl("data", names(object$call)))&&!(object$call["data"]=="sys.parent()()"))
{
# if (any(grepl("data", names(object$call)))) # new Mikis 25-3-13
# {
# if (object$call["data"]=="sys.parent()()") DataExist <- FALSE
# else
DaTa <- eval(object$call[["data"]]) #get(as.character(object$call["data"]))
DataExist <- TRUE
# }
}
# }
#else
# {
# DaTa <- data
#}
#-------------------------------------------------
## if xvar is null just plot the single worm plot
##--- case 1 -------------------------------------
# is(xvar, "formula") # OK works if it is
# with(DaTa, {substitute(xvar)})
# with(DaTa, eval(substitute(xvar))) NOT WORKING
# eval(substitute(xvar), envir=as.environment(DaTa)) # OK
#y <- if (!is.null(data)) get(deparse(substitute(y)), envir=as.environment(data)) else y
# grep("$", deparse(substitute(xvar)))
#TRYING <- try(is(xvar, "formula"))
#if (any(suppressMessages(class(TRYING)%in%"try-error")))
# the idea is to get xvar
# if xvar=NULL will work
# if xvar=data$variable it will work
# if xvar=variable you need to get it from the data
# if xvar=~formula then we are in trouble
if (!grepl("$", deparse(substitute(xvar)), fixed=T)&&!grepl("~", deparse(substitute(xvar)), fixed=T)&&DataExist)
{
xvar <- eval(substitute(xvar), envir=as.environment(DaTa))
}
#-------------------------------------------------------------------------------
if(is.null(xvar)) # if xvar=NULL
{
qq <- as.data.frame(qqnorm(resid, plot = FALSE))
qq$y <- qq$y - qq$x
level <- .95
lz <- -xlim.all
hz <- xlim.all
dz <- 0.25
z <- seq(lz,hz,dz)
p <- pnorm(z)
se <- (1/dnorm(z))*(sqrt(p*(1-p)/length(qq$y)))
low <- qnorm((1-level)/2)*se
high <- -low
if ( any(abs(qq$y)>ylim.all) )
{
warning("Some points are missed out ", "\n","increase the y limits using ylim.all" )
}
if ( any(abs(qq$x)>xlim.all) )
{
warning("Some points are missed out ", "\n","increase the x limits using xlim.all" )
}
plot(qq$x,qq$y,ylab="Deviation", xlab="Unit normal quantile",
xlim=c(-xlim.all,xlim.all), ylim=c(-ylim.all , ylim.all), cex=cex, pch=pch , bg = bg,cex.lab=cex.lab )
grid(lty = "solid")
abline(0, 0, lty = 2, col = col)
abline(0, 100000, lty = 2, col = col)
lines(z, low, lty=2)
lines(z, high, lty=2)
if(line == TRUE)
{
fit <- lm(qq$y ~ qq$x+I(qq$x^2)+I(qq$x^3)) #poly(qq$x,3))
s <- spline(qq$x, fitted(fit))
flags <- s$x > -xlim.all & s$x < xlim.all
lines(list(x = s$x[flags], y = s$y[flags]), col=col, lwd=.5)
}
return(invisible(coef(fit)))
}
##---------------------------------------------------------------------
## if xvar is not a formula then plot the old wp()
## ---- case 2 --------------------------------------------------------
if (!is(xvar,"formula")) # xvar =x or data$x
{
## get weights
if (is.factor(xvar)) stop("Use formula for factors i.e. xvar=~f")
w <- if (is.null(object)) rep(1, length(resid)) else object$weights # geting the weights
## if w=0 reduce if w=freq expand if all(w=1) same
## here we need the xvar
if (all(trunc(w)==w)) xvar <- rep(xvar, w)
if(is.null(xcut.points))
{ # getting the intervals automatic
given.in <- co.intervals(xvar, number=n.inter, overlap=overlap )
if (overlap==0) given.in <- check.overlap(given.in)
}
else
{ # if xcut.points is set
given.in <- get.intervals(xvar, xcut.points )
}
total.points <- 0
coef <- coef1<-NULL
y.y <- resid
x.x <- resid
coplot(y.y~x.x | xvar ,
given.values = given.in,
panel = panel.fun,
ylim = c(-ylim.worm, ylim.worm),
xlim = c(-xlim.worm, xlim.worm),
ylab = "Deviation",
xlab = "Unit normal quantile",
show.given = show.given,
bg = bg,
pch = pch,
cex = cex,
bar.bg = bar.bg)
if (overlap==0)
{
if (total.points!=length(resid))
warning("the total number of points in the plot is not equal \n to the number of observations in y \n")
}
mcoef <- matrix(coef,ncol=4,byrow=TRUE)
out <- list(classes = given.in, coef = mcoef)
return(invisible(out))
}
## if xvar is formula then plot the usual wp()
## ---- case 3 -------------------------------------------------
if (is(xvar,"formula"))
{
w <- if (is.null(object)) rep(1, length(resid)) else object$weights # geting the weights
## if w=0 reduce if w=freq expand if all(w=1) same
## expand the x's
## I have a problem here in that I can not expand easily the formula so I will stop it
# if (all(trunc(w)==w)) xvar <- rep(xvar, w)
total.points <- 0
coef <- coef1<-NULL
y.y <- resid
x.x <- resid
if (DataExist) #-------------------------------------------------DATA EXIST---
{
coplot(as.formula(paste("y.y~x.x|", as.character(xvar), sep="")[2]),
# given.values = given.in,
data = DaTa,
panel = panel.fun,
# given.values = xcut.points, this is not working pass it with given values
overlap = overlap,
number = n.inter,
ylim = c(-ylim.worm, ylim.worm),
xlim = c(-xlim.worm, xlim.worm),
ylab = "Deviation",
xlab = "Unit normal quantile",
show.given = show.given,
bg = bg,
pch = pch,
cex = cex,
bar.bg = bar.bg , ...)
mcoef <- matrix(coef,ncol=4,byrow=TRUE)
# classes = given.in,
if ("given.values"%in%names(vars <- list(...)))
given.in <- vars$given.values
else
{
rhs <- deparen(xvar)[[2L]]
if (length(rhs)==3&&rhs[[1]]!="$")
{
a <- eval(deparen(rhs[[2L]]), envir=as.environment(DaTa))
b <- eval(deparen(rhs[[3L]]), envir=as.environment(DaTa))
if (length(n.inter) == 1L) n.inter <- rep(n.inter, 2)
if (length(overlap) == 1L) overlap <- rep(overlap, 2)
Inter1 <- if (is.factor(a)) levels(a)
else co.intervals(unclass(a), number = n.inter[1L], overlap = overlap[1L])
Inter2 <- if (is.factor(b)) levels(b)
else co.intervals(unclass(b), number = n.inter[2L], overlap = overlap[2L])
given.in <- list(Inter1, Inter2)
}
else
{
a <- eval(deparen(rhs), envir=as.environment(DaTa))
if (length(n.inter) == 1L) n.inter <- rep(n.inter, 2)
if (length(overlap) == 1L) overlap <- rep(overlap, 2)
given.in <- if (is.factor(a)) levels(a)
else co.intervals(unclass(a), number = n.inter[1L], overlap = overlap[1L])
}
}
out <- list(classes = given.in, coef = mcoef) #classes = given.in,
return(invisible(out))
}#-------------------------------------------------DATA EXIST FINISH HERE
else #-------------------------------------------------DATA DO NOT EXIST-----
{
coplot(as.formula(paste("y.y~x.x|", as.character(xvar), sep="")[2]),
panel = panel.fun,
# given.values = xcut.points, this is not working pass it with given values
overlap = overlap,
number = n.inter,
ylim = c(-ylim.worm, ylim.worm),
xlim = c(-xlim.worm, xlim.worm),
ylab = "Deviation",
xlab = "Unit normal quantile",
show.given = show.given,
bg = bg,
pch = pch,
cex = cex,
bar.bg = bar.bg , ...)
mcoef <- matrix(coef,ncol=4,byrow=TRUE)
# classes = given.in,
if ("given.values"%in%names(vars <- list(...)))
given.in <- vars$given.values
else
{
rhs <- deparen(xvar)[[2L]]
if (length(rhs)==3&&rhs[[1]]!="$")
{
a <- eval(deparen(rhs[[2L]]))
b <- eval(deparen(rhs[[3L]]))
if (length(n.inter) == 1L) n.inter <- rep(n.inter, 2)
if (length(overlap) == 1L) overlap <- rep(overlap, 2)
Inter1 <- if (is.factor(a)) levels(a)
else co.intervals(unclass(a), number = n.inter[1L], overlap = overlap[1L])
Inter2 <- if (is.factor(b)) levels(b)
else co.intervals(unclass(b), number = n.inter[2L], overlap = overlap[2L])
given.in <- list(Inter1, Inter2)
}
else
{
a <- eval(deparen(rhs))
if (length(n.inter) == 1L) n.inter <- rep(n.inter, 2)
if (length(overlap) == 1L) overlap <- rep(overlap, 2)
given.in <- if (is.factor(a)) levels(a)
else co.intervals(unclass(a), number = n.inter[1L], overlap = overlap[1L])
}
}
out <- list(classes = given.in, coef = mcoef) #classes = given.in,
return(invisible(out))
}#-----------------------------------------------DATA GO NOT EXIST FINISH HERE
}#--------------------------------------------------------- FORMULA FINISH
}#--------------------------------------------------------- ENF FUNCTION
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#------------------------------------------------------------------------------------------
# Mikis Stasinopoulos
# last 10 - 5 - 13
#TO DO the weights with frequency i.e w=1,4,1,4,2,6
# is not implemented properly
# the idea here is to allow more that one variable in xvar
# this is achieved by using a formula specification for example ~Fl*A
# TO DO
# i) n.inter : what hapent in this case this is OK
# ii) xcut.points : OK it needs to use the argument
# iii) overlap : it seems is working
# iv) factor in xvar : OK
# also by increasing in the panel function lwd=.5 from lwd=.01 the plots are also shown in all versions rather than x11()
# This is a new version witch can take any object with resid()
# or the actual residuals using the argument resid
## worm plots based on the worm plot function in S-plus by Van Buuren and
## Fredriks (2001) Worm plot: a simple diagnostic device for modelling
## growth reference curves, Statist. Med.
## original created by Mikis Stasinopoulos and Bob Rigby, Friday, November 8, 2002.
## last change Tuersday
wp <- function ( object = NULL,
xvar = NULL,
resid = NULL,
n.inter = 4,
xcut.points = NULL,
overlap = 0,
xlim.all = 4,
xlim.worm = 3.5,
show.given = TRUE,
line = TRUE,
ylim.all = 12*sqrt(1/length(resid)),
ylim.worm = 12*sqrt(n.inter/length(resid)),
cex = 1,
cex.lab = 1,
pch = 21,
bg = "wheat",
col = "red",
bar.bg = c(num="light blue"),
...)
{
##-----------------------------------------------------------------------------
#------------------------------------------------------------------------------
# local functions
# i) panel.fun
# ii) check.overlap
# iii) get.intervals
#-----------------------------------------------------------------------------
panel.fun <- function (x, y, col = par("col"), bg = NA, pch = par("pch"),
cex = par("cex"), col.smooth = "red", span = 2/3, iter = 3, ...)
{
qq <- as.data.frame(qqnorm(y, plot = FALSE))
if(any(is.infinite(qq$y))) line <-FALSE # added 30-4-13 DS if any y Inf do not fit lm
qq$y <- qq$y - qq$x
grid(nx=NA,ny=NA, lwd = 2) # grid only in y-direction
# points(qq$x, qq$y, pch = 1, col = col, bg = bg, cex = 0.7)
points(qq$x, qq$y, pch = pch, col = col, bg = bg, cex = cex)
abline(0, 0, lty = 2, col = col)
abline(0, 100000, lty = 2, col = col)
yuplim <- 10*sqrt(1/length(qq$y))
level <- .95
lz <- -xlim.worm
# lz <- -2.75
hz <- xlim.worm
# hz <- 2.75
dz <- 0.25
z <- seq(lz,hz,dz)
p <- pnorm(z)
se <- (1/dnorm(z))*(sqrt(p*(1-p)/length(qq$y)))
low <- qnorm((1-level)/2)*se
high <- -low
# if ( any(abs(qq$y)>ylim.worm) )
{
no.points <- length(qq$y)
total.points <<- total.points+no.points
no.mis <- sum(abs(qq$y)>ylim.worm)
cat("number of missing points from plot=", no.mis," out of ",no.points,"\n")
if ( any(abs(qq$y)>ylim.worm) ) warning("Some points are missed out ", "\n","increase the y limits using ylim.worm" )
}
if ( any(abs(qq$x)>xlim.worm) )
{
warning("Some points are missed out ", "\n","increase the x limits using xlim.worm" )
}
# se <- (1/dnorm(z))*(sqrt(p*(1-p)*n.inter/length(xvar)))
# low <- qnorm((1-level)/2)*se
# high <- -low
lines(z, low, lty=2, lwd=.5)
lines(z, high, lty=2, lwd=.5)
if(line == TRUE)
{
fit <- lm(y ~ x+I(x^2)+I(x^3), data=qq) #poly(qq$x,3))
s <- spline(qq$x, fitted(fit))
flags <- s$x > -2.5 & s$x < 2.5
lines(list(x = s$x[flags], y = s$y[flags]), col=col, lwd=.5)
assign("coef1",coef(fit),envir = parent.frame(n=3))
assign("coef" , c(coef, coef1),envir = parent.frame(n=3))
}
}
##-----------------------------------------------------------------------------
check.overlap <- function(interval)
{
if (!is.matrix(interval) ) {stop(paste("The interval specified is not a matrix."))}
if (dim(interval)[2] !=2) {stop(paste("The interval specified is not a valid matrix.\nThe number of columns should be equal to 2."))}
crows = dim(interval)[1]
for (i in 1:(crows-1))
{
#if (interval[i,2] != interval[i+1,1]) {interval[i+1,1]=interval[i,2]}
if (!(abs(interval[i,2]-interval[i+1,1])<0.0001)) {interval[i+1,1]=interval[i,2]}
}
return(interval)
}
##-----------------------------------------------------------------------------=
# the problem here is that coplot uses for given.values MS Tuesday, September 21, 2004
# min <= x <= 20 min <= x < 20 min <= x <= 20-extra
# 20 <= x <= 30 instead of 20 <= x < 30 here uses 20 <= x <= 30-extra
# 30 <= x <= max 30 <= x <= max 30 <= x <= max+extra
get.intervals <- function (xvar, xcut.points )
{
if (!is.vector(xcut.points)) {stop(paste("The interval is not a vector."))}
if ( any((xcut.points < min(xvar)) | any(xcut.points > max(xvar))))
{stop(paste("The specified `xcut.points' are not within the range of the x: (", min(xvar),
" , ", max(xvar), ")"))}
extra <- (max(xvar)-min(xvar))/100000
int <- c(min(xvar), xcut.points, (max(xvar)+2*extra))
ii <- 1:(length(int)-1)
r <- 2:length(int)
x1 <- int[ii]
xr <- int[r]-extra
if (any(x1>xr)) {stop(paste("The interval is are not in a increasing order."))}
cbind(x1,xr)
}
##------------------------------------------------------------------------------
# this function comes from coplot() to help to get the variables used if more that one xvar is used
deparen <- function(expr)
{
while (is.language(expr) && !is.name(expr) && deparse(expr[[1L]])[1L] ==
"(") expr <- expr[[2L]]
expr
}
##------------------------------------------------------------------------------
##-here is the main function ---------------------------------------------------
#-------------------------------------------------------------------------------
## get residuals
if (is.null(object)&&is.null(resid)) stop(paste("A fitted object with resid() method or the argument resid should be used ", "\n", ""))
resid <- if (is.null(object)) resid else resid(object)
DataExist <- FALSE
## get data if exist
#if (is.null(data))
# {
if (!is.null(object)&&any(grepl("data", names(object$call)))&&!(object$call["data"]=="sys.parent()()"))
{
# if (any(grepl("data", names(object$call)))) # new Mikis 25-3-13
# {
# if (object$call["data"]=="sys.parent()()") DataExist <- FALSE
# else
DaTa <- eval(object$call[["data"]]) #get(as.character(object$call["data"]))
DataExist <- TRUE
# }
}
# }
#else
# {
# DaTa <- data
#}
#-------------------------------------------------
## if xvar is null just plot the single worm plot
##--- case 1 -------------------------------------
# is(xvar, "formula") # OK works if it is
# with(DaTa, {substitute(xvar)})
# with(DaTa, eval(substitute(xvar))) NOT WORKING
# eval(substitute(xvar), envir=as.environment(DaTa)) # OK
#y <- if (!is.null(data)) get(deparse(substitute(y)), envir=as.environment(data)) else y
# grep("$", deparse(substitute(xvar)))
#TRYING <- try(is(xvar, "formula"))
#if (any(suppressMessages(class(TRYING)%in%"try-error")))
# the idea is to get xvar
# if xvar=NULL will work
# if xvar=data$variable it will work
# if xvar=variable you need to get it from the data
# if xvar=~formula then we are in trouble
if (!grepl("$", deparse(substitute(xvar)), fixed=T)&&!grepl("~", deparse(substitute(xvar)), fixed=T)&&DataExist)
{
xvar <- eval(substitute(xvar), envir=as.environment(DaTa))
}
#-------------------------------------------------------------------------------
if(is.null(xvar)) # if xvar=NULL
{
qq <- as.data.frame(qqnorm(resid, plot = FALSE))
qq$y <- qq$y - qq$x
level <- .95
lz <- -xlim.all
hz <- xlim.all
dz <- 0.25
z <- seq(lz,hz,dz)
p <- pnorm(z)
se <- (1/dnorm(z))*(sqrt(p*(1-p)/length(qq$y)))
low <- qnorm((1-level)/2)*se
high <- -low
if ( any(abs(qq$y)>ylim.all) )
{
warning("Some points are missed out ", "\n","increase the y limits using ylim.all" )
}
if ( any(abs(qq$x)>xlim.all) )
{
warning("Some points are missed out ", "\n","increase the x limits using xlim.all" )
}
plot(qq$x,qq$y,ylab="Deviation", xlab="Unit normal quantile",
xlim=c(-xlim.all,xlim.all), ylim=c(-ylim.all , ylim.all), cex=cex, pch=pch , bg = bg,cex.lab=cex.lab )
grid(lty = "solid")
abline(0, 0, lty = 2, col = col)
abline(0, 100000, lty = 2, col = col)
lines(z, low, lty=2)
lines(z, high, lty=2)
if(line == TRUE)
{
fit <- lm(qq$y ~ qq$x+I(qq$x^2)+I(qq$x^3)) #poly(qq$x,3))
s <- spline(qq$x, fitted(fit))
flags <- s$x > -xlim.all & s$x < xlim.all
lines(list(x = s$x[flags], y = s$y[flags]), col=col, lwd=.5)
}
return(invisible(coef(fit)))
}
##---------------------------------------------------------------------
## if xvar is not a formula then plot the old wp()
## ---- case 2 --------------------------------------------------------
if (!is(xvar,"formula")) # xvar =x or data$x
{
## get weights
if (is.factor(xvar)) stop("Use formula for factors i.e. xvar=~f")
w <- if (is.null(object)) rep(1, length(resid)) else object$weights # geting the weights
## if w=0 reduce if w=freq expand if all(w=1) same
## here we need the xvar
if (all(trunc(w)==w)) xvar <- rep(xvar, w)
if(is.null(xcut.points))
{ # getting the intervals automatic
given.in <- co.intervals(xvar, number=n.inter, overlap=overlap )
if (overlap==0) given.in <- check.overlap(given.in)
}
else
{ # if xcut.points is set
given.in <- get.intervals(xvar, xcut.points )
}
total.points <- 0
coef <- coef1<-NULL
y.y <- resid
x.x <- resid
coplot(y.y~x.x | xvar ,
given.values = given.in,
panel = panel.fun,
ylim = c(-ylim.worm, ylim.worm),
xlim = c(-xlim.worm, xlim.worm),
ylab = "Deviation",
xlab = "Unit normal quantile",
show.given = show.given,
bg = bg,
pch = pch,
cex = cex,
bar.bg = bar.bg)
if (overlap==0)
{
if (total.points!=length(resid))
warning("the total number of points in the plot is not equal \n to the number of observations in y \n")
}
mcoef <- matrix(coef,ncol=4,byrow=TRUE)
out <- list(classes = given.in, coef = mcoef)
return(invisible(out))
}
## if xvar is formula then plot the usual wp()
## ---- case 3 -------------------------------------------------
if (is(xvar,"formula"))
{
w <- if (is.null(object)) rep(1, length(resid)) else object$weights # geting the weights
## if w=0 reduce if w=freq expand if all(w=1) same
## expand the x's
## I have a problem here in that I can not expand easily the formula so I will stop it
# if (all(trunc(w)==w)) xvar <- rep(xvar, w)
total.points <- 0
coef <- coef1<-NULL
y.y <- resid
x.x <- resid
if (DataExist) #-------------------------------------------------DATA EXIST---
{
coplot(as.formula(paste("y.y~x.x|", as.character(xvar), sep="")[2]),
# given.values = given.in,
data = DaTa,
panel = panel.fun,
# given.values = xcut.points, this is not working pass it with given values
overlap = overlap,
number = n.inter,
ylim = c(-ylim.worm, ylim.worm),
xlim = c(-xlim.worm, xlim.worm),
ylab = "Deviation",
xlab = "Unit normal quantile",
show.given = show.given,
bg = bg,
pch = pch,
cex = cex,
bar.bg = bar.bg , ...)
mcoef <- matrix(coef,ncol=4,byrow=TRUE)
# classes = given.in,
if ("given.values"%in%names(vars <- list(...)))
given.in <- vars$given.values
else
{
rhs <- deparen(xvar)[[2L]]
if (length(rhs)==3&&rhs[[1]]!="$")
{
a <- eval(deparen(rhs[[2L]]), envir=as.environment(DaTa))
b <- eval(deparen(rhs[[3L]]), envir=as.environment(DaTa))
if (length(n.inter) == 1L) n.inter <- rep(n.inter, 2)
if (length(overlap) == 1L) overlap <- rep(overlap, 2)
Inter1 <- if (is.factor(a)) levels(a)
else co.intervals(unclass(a), number = n.inter[1L], overlap = overlap[1L])
Inter2 <- if (is.factor(b)) levels(b)
else co.intervals(unclass(b), number = n.inter[2L], overlap = overlap[2L])
given.in <- list(Inter1, Inter2)
}
else
{
a <- eval(deparen(rhs), envir=as.environment(DaTa))
if (length(n.inter) == 1L) n.inter <- rep(n.inter, 2)
if (length(overlap) == 1L) overlap <- rep(overlap, 2)
given.in <- if (is.factor(a)) levels(a)
else co.intervals(unclass(a), number = n.inter[1L], overlap = overlap[1L])
}
}
out <- list(classes = given.in, coef = mcoef) #classes = given.in,
return(invisible(out))
}#-------------------------------------------------DATA EXIST FINISH HERE
else #-------------------------------------------------DATA DO NOT EXIST-----
{
coplot(as.formula(paste("y.y~x.x|", as.character(xvar), sep="")[2]),
panel = panel.fun,
# given.values = xcut.points, this is not working pass it with given values
overlap = overlap,
number = n.inter,
ylim = c(-ylim.worm, ylim.worm),
xlim = c(-xlim.worm, xlim.worm),
ylab = "Deviation",
xlab = "Unit normal quantile",
show.given = show.given,
bg = bg,
pch = pch,
cex = cex,
bar.bg = bar.bg , ...)
mcoef <- matrix(coef,ncol=4,byrow=TRUE)
# classes = given.in,
if ("given.values"%in%names(vars <- list(...)))
given.in <- vars$given.values
else
{
rhs <- deparen(xvar)[[2L]]
if (length(rhs)==3&&rhs[[1]]!="$")
{
a <- eval(deparen(rhs[[2L]]))
b <- eval(deparen(rhs[[3L]]))
if (length(n.inter) == 1L) n.inter <- rep(n.inter, 2)
if (length(overlap) == 1L) overlap <- rep(overlap, 2)
Inter1 <- if (is.factor(a)) levels(a)
else co.intervals(unclass(a), number = n.inter[1L], overlap = overlap[1L])
Inter2 <- if (is.factor(b)) levels(b)
else co.intervals(unclass(b), number = n.inter[2L], overlap = overlap[2L])
given.in <- list(Inter1, Inter2)
}
else
{
a <- eval(deparen(rhs))
if (length(n.inter) == 1L) n.inter <- rep(n.inter, 2)
if (length(overlap) == 1L) overlap <- rep(overlap, 2)
given.in <- if (is.factor(a)) levels(a)
else co.intervals(unclass(a), number = n.inter[1L], overlap = overlap[1L])
}
}
out <- list(classes = given.in, coef = mcoef) #classes = given.in,
return(invisible(out))
}#-----------------------------------------------DATA GO NOT EXIST FINISH HERE
}#--------------------------------------------------------- FORMULA FINISH
}#--------------------------------------------------------- ENF FUNCTION
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