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# Package: ldr
# Type: Package
# Title: Methods for likelihood-based dimension reduction in regression
# Version: 1.3.3
# Date: 2014-06-06
# Author: Kofi Placid Adragni, Andrew Raim
# Maintainer: Kofi Placid Adragni <kofi@umbc.edu>
# Description: Functions, methods, and data sets for fitting likelihood-based dimension reduction in regression,
# using principal fitted components (pfc), likelihood acquired directions (lad), covariance reducing models (core).
# URL: https://www.jstatsoft.org/v61/i03/
# License: GPL (>= 2)
# Packaged: 2021-10-08 16:32:42 UTC; Nathan
# Repository: https://github.com/cran/ldr
# Date/Publication: 2014-10-29 16:36:14
#
# Divides a vector of length n into slices of approximately equal size.
# It is used to construct the piecewise bases, and internally used in lad functions.
#
ldr.slices <-
function(y, nslices=3)
{
endpoints <- function(n, nslices)
{
# This function is intended to determine the end-points of the slices.
increment <- floor(n/nslices)
if (nslices ==1) return(n)
if (nslices > 1)
{
ends<- seq(1:nslices)*increment
rest <- n%%nslices
if (rest==0) return(ends)
if (rest>0)
{
for (i in 1:rest) ends[i]<-ends[i]+i
for (i in (rest+1):nslices) ends[i]<- ends[i]+rest
return(ends)
}
}
}
n <- length(y)
indicators <- vector(length=n)
sorty <- sort(y)
bins.y <- vector("list", nslices)
ends <- endpoints(n, nslices)
if (nslices==1)
{
bins.y[[1]] <- sorty[1:ends[1]]
indicators[1:ends[1]]<-1
return(list(bins=bins.y, nslices=nslices, slice.size=n, slice.indicator=indicators[rank(y)]))
}
else if (nslices==2)
{
bins.y[[1]] <- sorty[1:ends[1]]
bins.y[[2]] <- sorty[(ends[1]+1):ends[2]]
indicators[1:ends[1]]<-1
indicators[(ends[1]+1):ends[2]]<-2
return(list(bins=bins.y, nslices=nslices, slice.size=diff(c(0,ends)), slice.indicator=indicators[rank(y)]))
}
else
{
bins.y[[1]] <- sorty[1:(ends[1]-1)]
indicators[1:(ends[1]-1)]<-1
for (i in 2:(nslices-1))
{
bins.y[[i]] <- sorty[ends[i-1]:(ends[i]-1)]
indicators[ends[i-1]:(ends[i]-1)] <- i
}
bins.y[[nslices]] <- sorty[ends[nslices-1]:(ends[nslices])]
indicators[ends[nslices-1]:(ends[nslices])] <- nslices
return(list(bins=bins.y, nslices=nslices, slice.size=diff(c(0,ends)), slice.indicator=indicators[rank(y)]))
}
}
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