block_pca: block_pca

In bbuchsbaum/neuropls: neuroca: multiblock component analysis for neuroimaging data

block_pca

Description

block_pca

Usage

block_pca(
  X,
  est_method = c("gcv", "shrink", "fixed", "nneg"),
  ncomp = 2,
  min_k = 1,
  max_k = 3,
  center = TRUE,
  scale = FALSE,
  shrink_method = "GSURE",
  ...
)

Arguments

X	the data matrix and instance of class block_matrix
est_method	the pca method to apply to each block
ncomp	the number of components to extract from each block (can vary by block or be fixed)
min_k	the minimum number of components in each block
max_k	the maximum number of components in each block
center	whether to center columns
scale	whether to scale columns

bbuchsbaum/neuropls documentation built on April 17, 2022, 8:46 a.m.