scada: scada

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

scada

Description

simulataneous component discriminant analysis

Usage

scada(
  Y,
  Xlist,
  ncomp = 2,
  center = TRUE,
  scale = FALSE,
  rank_k = NULL,
  type = c("sca-p", "sca-pf2", "sca-ind", "sca-ecp")
)

Arguments

Y	dependent factor variable. If All X matrices have same number of rows, Y can be a single factor. If there are a different number of rows (e.g. different numbers of replications per subject), Y can be a list of factors.
Xlist	a list of X matrices, one per subject.
ncomp	number of common components to estimate
center	whether to center the variables
scale	whether to scale the variables by 1/sd
rank_k	reduce data to k components per block via pca
normalization	the type of normalization

bbuchsbaum/neuroca documentation built on April 22, 2022, 2:50 a.m.