Nothing
#############################################################
# #
# wle.cp function #
# Author: Claudio Agostinelli #
# E-mail: claudio@unive.it #
# Date: October, 15, 2012 #
# Version: 0.6 #
# #
# Copyright (C) 2012 Claudio Agostinelli #
# #
#############################################################
wle.cp <- function(formula, data=list(), model=TRUE, x=FALSE, y=FALSE, boot=30, group, var.full=0, num.sol=1, raf="HD", smooth=0.031, tol=10^(-6), equal=10^(-3), max.iter=500, min.weight=0.5, method="full", alpha=2, contrasts=NULL, verbose=FALSE) {
raf <- switch(raf,
HD = 1,
NED = 2,
SCHI2 = 3,
-1)
if (raf==-1) stop("Please, choose the RAF: HD=Hellinger Disparity, NED=Negative Exponential Disparity, SCHI2=Symmetric Chi-squares Disparity")
type <- switch(method,
full = 0,
reduced = 1,
-1)
if (type==-1) stop("Please, choose the method: full=wieghts based on full model, reduced=weights based on the actual model")
if (missing(group)) {
group <- 0
}
ret.x <- x
ret.y <- y
result <- list()
mt <- terms(formula, data = data)
mf <- cl <- match.call()
mf$boot <- mf$group <- mf$smooth <- NULL
mf$tol <- mf$equal <- mf$num.sol <- NULL
mf$min.weight <- mf$max.iter <- mf$raf <- NULL
mf$var.full <- mf$alpha <- mf$contrasts <- NULL
mf$model <- mf$x <- mf$y <- mf$method <- NULL
mf$verbose <- NULL
mf$drop.unused.levels <- TRUE
mf[[1]] <- as.name("model.frame")
mf <- eval(mf, sys.frame(sys.parent()))
xvars <- as.character(attr(mt, "variables"))[-1]
inter <- attr(mt, "intercept")
if((yvar <- attr(mt, "response")) > 0) xvars <- xvars[-yvar]
xlev <-
if(length(xvars) > 0) {
xlev <- lapply(mf[xvars], levels)
xlev[!sapply(xlev, is.null)]
}
ydata <- model.response(mf, "numeric")
if (is.empty.model(mt))
stop("The model is empty")
else
xdata <- model.matrix(mt, mf, contrasts)
if (is.null(size <- nrow(xdata)) | is.null(nvar <- ncol(xdata))) stop("'x' must be a matrix")
if (length(ydata)!=size) stop("'y' and 'x' are not compatible")
nrep <- 2^nvar-1
if (size<nvar) {
stop("Number of observations must be at least equal to the number of predictors (including intercept)")
}
if (group<nvar) {
group <- max(round(size/4),nvar)
if (verbose) cat("wle.cp: dimension of the subsample set to default value = ",group,"\n")
}
maxboot <- sum(log(1:size))-(sum(log(1:group))+sum(log(1:(size-group))))
if (boot<1 | log(boot) > maxboot) {
stop("Bootstrap replication not in the range")
}
if (!(num.sol>=1)) {
if (verbose) cat("wle.cp: number of solution to report set to 1 \n")
num.sol <- 1
}
if (max.iter<1) {
if (verbose) cat("wle.cp: max number of iteration set to 500 \n")
max.iter <- 500
}
if (smooth<10^(-5)) {
if (verbose) cat("wle.cp: the smooth parameter seems too small \n")
}
if (tol<=0) {
if (verbose) cat("wle.cp: the accuracy must be positive, using default value: 10^(-6) \n")
tol <- 10^(-6)
}
if (equal<=tol) {
if (verbose) cat("wle.cp: the equal parameter must be greater than tol, using default value: tol+10^(-3)\n")
equal <- tol+10^(-3)
}
if (var.full<0) {
if (verbose) cat("wle.cp: the variance of the full model can not be negative, using default value \n")
var.full <- 0
}
if (min.weight<0) {
if (verbose) cat("wle.cp: the minimum sum of the weights can not be negative, using default value \n")
min.weight <- 0.5
}
z <- .Fortran("wlecp",
as.double(ydata),
as.matrix(xdata),
as.integer(0),
as.integer(size),
as.integer(nvar),
as.integer(boot),
as.integer(group),
as.integer(nrep),
as.integer(raf),
as.double(smooth),
as.double(tol),
as.double(equal),
as.integer(max.iter),
as.double(var.full),
as.integer(num.sol),
as.double(min.weight),
as.integer(type),
as.double(alpha),
wcp=mat.or.vec(nrep*num.sol,nvar+1),
param=mat.or.vec(nrep*num.sol,nvar),
var=double(nrep*num.sol),
resid=mat.or.vec(nrep*num.sol,size),
totweight=double(nrep*num.sol),
weight=mat.or.vec(nrep*num.sol,size),
same=integer(nrep*num.sol),
info=integer(1),
PACKAGE = "wle")
delnull <- which(z$same==0)
if (length(delnull)) {
z$wcp <- z$wcp[-delnull,]
z$param <- z$param[-delnull,]
z$var <- z$var[-delnull]
z$resid <- z$resid[-delnull]
z$weight <- z$weight[-delnull,]
z$totweight <- z$totweight[-delnull]
}
result$wcp <- z$wcp
result$coefficients <- z$param
result$scale <- sqrt(z$var)
result$residuals <- z$resid
result$weights <- z$weight
result$tot.weights <- z$totweight
result$freq <- z$same
result$call <- cl
result$info <- z$info
result$contrasts <- attr(xdata, "contrasts")
result$xlevels <- xlev
result$terms <- mt
if (model)
result$model <- mf
if (ret.x)
result$x <- xdata
if (ret.y)
result$y <- ydata
dn <- colnames(xdata)
dimnames(result$coefficients) <- list(NULL,dn)
dimnames(result$wcp) <- list(NULL,c(dn,"wcp"))
class(result) <- "wle.cp"
return(result)
}
#############################################################
# #
# summary.wle.cp function #
# Author: Claudio Agostinelli #
# E-mail: claudio@unive.it #
# Date: October, 28, 2003 #
# Version: 0.4-1 #
# #
# Copyright (C) 2003 Claudio Agostinelli #
# #
#############################################################
summary.wle.cp <- function (object, num.max=20, verbose=FALSE, ...) {
if (is.null(object$terms)) {
stop("invalid \'wle.cp\' object")
}
if (num.max<1) {
if (verbose) cat("summary.wle.cp: num.max can not less than 1, num.max=1 \n")
num.max <- 1
}
ans <- list()
wcp <- object$wcp
if(is.null(nmodel <- nrow(wcp))) nmodel <- 1
num.max <- min(nmodel,num.max)
if (nmodel!=1) {
nvar <- ncol(wcp)-1
nparam <- apply(wcp[,(1:nvar)],1,sum)
wcp <- wcp[wcp[,(nvar+1)]<=(nparam+0.00001),]
if (!is.null(nrow(wcp)) && nrow(wcp)>1) {
num.max <- min(nrow(wcp),num.max)
wcp <- wcp[order(wcp[,(nvar+1)]),]
wcp <- wcp[1:num.max,]
} else num.max <- 1
}
ans$wcp <- wcp
ans$num.max <- num.max
ans$call <- object$call
class(ans) <- "summary.wle.cp"
return(ans)
}
#############################################################
# #
# print.wle.cp function #
# Author: Claudio Agostinelli #
# E-mail: claudio@unive.it #
# Date: October, 27, 2003 #
# Version: 0.4-1 #
# #
# Copyright (C) 2003 Claudio Agostinelli #
# #
#############################################################
print.wle.cp <- function (x, digits = max(3, getOption("digits") - 3), num.max=max(1, nrow(x$wcp)), ...) {
res <- summary.wle.cp(object=x, num.max=num.max, ...)
print.summary.wle.cp(res, digits=digits, ...)
}
#############################################################
# #
# print.summary.wle.cp function #
# Author: Claudio Agostinelli #
# E-mail: claudio@unive.it #
# Date: August, 2, 2001 #
# Version: 0.4 #
# #
# Copyright (C) 2001 Claudio Agostinelli #
# #
#############################################################
print.summary.wle.cp <- function (x, digits = max(3, getOption("digits") - 3), ...) {
cat("\nCall:\n")
cat(paste(deparse(x$call), sep="\n", collapse = "\n"), "\n\n", sep="")
cat("\nWeighted Mallows Cp:\n")
if(x$num.max>1) {
nvar <- ncol(x$wcp)-1
x$wcp[,(nvar+1)] <- signif(x$wcp[,(nvar+1)],digits)
} else {
nvar <- length(x$wcp)-1
x$wcp[(nvar+1)] <- signif(x$wcp[(nvar+1)],digits)
}
print(x$wcp)
cat("\n")
cat("Printed the first ",x$num.max," best models \n")
invisible(x)
}
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.