princomp.rmult {compositions} | R Documentation

## Principal component analysis for real data

### Description

Performs a principal component analysis for datasets of type rmult.

### Usage

    ## S3 method for class 'rmult':
    princomp(x,...)

### Arguments

`x` | a rmult-dataset
`...` | Further arguments to call `princomp.default`

### Details

The function just does `princomp(unclass(x),...,scale=scale)` and is only here for convenience.

### Value

An object of type `princomp` with the following fields

`sdev` | the standard deviation of the principal components.
`loadings` | the matrix of variable loadings (i.e., a matrix whose columns contain the eigenvectors). This is of class `"loadings"`.
`center` | the mean that was substracted from the data set
`scale` | the scaling applied to each variable
`n.obs` | number of observations
`scores` | if `scores = TRUE`, the scores of the supplied data on the principal components. Scores are coordinates in a basis given by the principal components.
`call` | the matched call
`na.action` | Not clearly understood

### Author(s)

K.Gerald v.d. Boogaart http://www.stat.boogaart.de

### See Also

`princomp.rplus`

### Examples

    data(SimulatedAmounts)
    pc <- princomp(rmult(sa.lognormals5))
    pc
    summary(pc)
    plot(pc)
    screeplot(pc)
    screeplot(pc,type="l")
    biplot(pc)
    biplot(pc,choice=c(1,3))
    loadings(pc)
    plot(loadings(pc))
    pc$sdev^2
    cov(predict(pc,sa.lognormals5))

[Package compositions version 0.91-6 Index]