flexible_mpm: Principal component analysis of a matrix

In Paradigm4/insight: SciDB REVEAL/Genomics API

Description

This function is a modified version of function mpm(). Depending upon requirement one can use the default PCA computation method of mpm() for analyzing all PCs or use a truncated PCA.

Usage

flexible_mpm(
  data,
  logtrans = TRUE,
  logrepl = 1e-09,
  center = c("double", "row", "column", "global", "none"),
  normal = c("global", "row", "column", "none"),
  closure = c("none", "row", "column", "global", "double"),
  row.weight = c("constant", "mean", "median", "max", "logmean", "RW"),
  col.weight = c("constant", "mean", "median", "max", "logmean", "CW"),
  CW = rep(1, ncol(data) - 1),
  RW = rep(1, nrow(data)),
  pos.row = rep(FALSE, nrow(data)),
  pos.column = rep(FALSE, ncol(data) - 1),
  svd.method = "default_svd",
  max.PC = 20
)

Arguments

svd.method	character; character indicating the algorithm to be used for PCA. Valid inputs are 'default_svd' and 'truncated_svd'. For 'truncated_svd' the number of principal components computed is equivalent to the value of the parameter max.PC.
max.PC	numeric; number of principal components to compute in case of truncated PCA. Default: 20

Details

flexible_mpm

Note

All other parameters of this function are same as that of function mpm().

Paradigm4/insight documentation built on April 5, 2020, 1:12 p.m.