svyprcomp: Sampling-weighted principal component analysis

In bschneidr/fastsurvey: Analysis of Complex Survey Samples

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)

bschneidr/fastsurvey documentation built on March 13, 2024, 11:12 a.m.