R: Sampling-weighted principal component analysis

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 3.32-1 Index]