svyprcomp {survey}R Documentation

Sampling-weighted principal component analysis

Description

Computes principal components using the sampling weights.

Usage

svyprcomp(formula, design, center = TRUE, scale. = FALSE, tol = NULL, scores = FALSE, ...)
## S3 method for class 'svyprcomp':
biplot(x, cols=c("black","darkred"),xlabs=NULL,weight=c("transparent","scaled","none"),
                           max.alpha=0.5,max.cex=0.5,xlim=NULL,ylim=NULL,pc.biplot=FALSE,expand=1,xlab=NULL,ylab=NULL,
                           arrow.len=0.1,
                           ...)

Arguments

formula model formula describing variables to be used
design survey design object.
center Center data before analysis?
scale. Scale to unit variance before analysis?
tol Tolerance for omitting components from the results; a proportion of the standard deviation of the first component. The default is to keep all components.
scores Return scores on each component? These are needed for biplot.
x A svyprcomp object
cols Base colors for observations and variables respectively
xlabs Formula, or character vector, giving labels for each observation
weight How to display the sampling weights: "scaled" changes the size of the point label, "transparent" uses opacity proportional to sampling weight, "none" changes neither.
max.alpha Opacity for the largest sampling weight, or for all points if weight!="transparent"
max.cex Character size (as a multiple of par("cex")) for the largest sampling weight, or for all points if weight!="scaled"
xlim,ylim,xlab,ylab Graphical parameters
expand,arrow.len See biplot
pc.biplot See link{biplot.prcomp}
... Other arguments to prcomp, or graphical parameters for biplot

Value

svyprcomp returns an object of class svyprcomp, similar to class prcomp but including design information

See Also

prcomp, biplot.prcomp

Examples

data(api)
dclus2<-svydesign(id=~dnum+snum, fpc=~fpc1+fpc2, data=apiclus2)

pc <- svyprcomp(~api99+api00+ell+hsg+meals+emer, design=dclus2,scale=TRUE,scores=TRUE)
pc
biplot(pc, xlabs=~dnum, weight="none")

biplot(pc, xlabs=~dnum,max.alpha=1)

biplot(pc, weight="scaled",max.cex=1.5, xlabs=~dnum)


[Package survey version 3.20 Index]