rpca {pbdML}R Documentation

Random PCA

Description

Random PCA

Usage

rpca(x, k = 1, q = 3, retx = TRUE, center = TRUE, scale = FALSE)

Arguments

x

The input data matrix.

k

The number of singular values and/or left/right singular vectors to estimate.

q

An integer exponent, say 1, 2, or 3. See the paper for details.

retx

Logical; determines if the rotated data should be returned.

center, scale

Logical; determines if the data should be centered/scaled first.

Value

An object of class prcomp.

Author(s)

Drew Schmidt

References

Halko, Martinsson, and Tropp. 2011. Finding structure with randomness: probabilistic algorithms for constructing approximate matrix decompositions. SIAM Review 53 217-288.

Duda, R. O., Hart, P. E., & Stork, D. G. (2012). Pattern classification, chapter 10. John Wiley & Sons.

Examples

## Not run: 
x <- matrix(rnorm(30), 10)

rpca(x)

## End(Not run)


[Package pbdML version 0.1-0 Index]