lol.utils.decomp: A utility to use irlba when necessary
In lolR: Linear Optimal Low-Rank Projection

A utility to use irlba when necessary

lol.utils.decomp(
  X,
  xfm = FALSE,
  xfm.opts = list(),
  ncomp = 0,
  t = 0.05,
  robust = FALSE
)

`X`	the data to compute the svd of.
`xfm`	whether to transform the variables before taking the SVD. FALSEapply no transform to the variables. 'unit'unit transform the variables, defaulting to centering and scaling to mean 0, variance 1. See `scale` for details and optional args. 'log'log-transform the variables, for use-cases such as having high variance in larger values. Defaults to natural logarithm. See `log` for details and optional args. 'rank'rank-transform the variables. Defalts to breaking ties with the average rank of the tied values. See `rank` for details and optional args. c(opt1, opt2, etc.)apply the transform specified in opt1, followed by opt2, etc.
`xfm.opts`	optional arguments to pass to the `xfm` option specified. Should be a numbered list of lists, where `xfm.opts[[i]]` corresponds to the optional arguments for `xfm[i]`. Defaults to the default options for each transform scheme.
`ncomp`	the number of left singular vectors to retain.
`t`	the threshold of percent of singular vals/vecs to use irlba.
`robust`	whether to use a robust estimate of the covariance matrix when taking PCA. Defaults to `FALSE`.