prcomp {matter} | R Documentation

## Principal Components Analysis for “matter” Matrices

### Description

This method allows computation of a truncated principal components analysis of a `matter_mat` matrix using the implicitly restarted Lanczos method `irlba`.

### Usage

    ## S4 method for signature 'matter_mat'
    prcomp(x, n = 3, retx = TRUE, center = TRUE, scale. = FALSE, ...)

### Arguments

`x` | A `matter` matrix.
`n` | The number of principal componenets to return, must be less than `min(dim(x))`.
`retx` | A logical value indicating whether the rotated variables should be returned.
`center` | A logical value indicating whether the variables should be shifted to be zero-centered, or a centering vector of length equal to the number of columns of `x`. The centering is performed implicitly and does not change the out-of-memory data in `x`.
`scale.` | A logical value indicating whether the variables should be scaled to have unit variance, or a scaling vector of length equal to the number of columns of `x`. The scaling is performed implicitly and does not change the out-of-memory data in `x`.
`...` | Additional options passed to `irlba`.

### Value

An object of class ‘prcomp’. See `?prcomp` for details.

### Note

The 'tol' truncation argument found in the default `prcomp` method is not supported. In place of the truncation tolerance in the original function, the argument `n` explicitly gives the number of principal components to return. A warning is generated if the argument 'tol' is used.

### Author(s)

Kylie A. Bemis

### See Also

`bigglm`

### Examples

    set.seed(1)

    x <- matter_mat(rnorm(1000), nrow=100, ncol=10)

    prcomp(x)

[Package matter version 1.18.0 Index]