GenerateToyData: Generate 'Toy' Data

In CJIVE: Canonical Joint and Individual Variation Explained (CJIVE)

Generate 'Toy' Data

Description

Generates two Simulated Datasets that follow JIVE Model using binary subject scores

Usage

GenerateToyData(
  n,
  p1,
  p2,
  JntVarEx1,
  JntVarEx2,
  IndVarEx1,
  IndVarEx2,
  jnt_rank = 1,
  equal.eig = FALSE,
  ind_rank1 = 2,
  ind_rank2 = 2,
  SVD.plots = TRUE,
  Error = TRUE,
  print.cor = TRUE
)

Arguments

n	integer for sample size, i.e. number of subjects
p1	integer for number of features/variables in first data set
p2	integer for number of features/variables in second data set
JntVarEx1	numeric between (0,1) which describes proportion of variance in the first data set which is attributable to the joint signal
JntVarEx2	numeric between (0,1) which describes proportion of variance in the second data set which is attributable to the joint signal
IndVarEx1	numeric between (0,1) which describes proportion of variance in the first data set which is attributable to the individual signal
IndVarEx2	numeric between (0,1) which describes proportion of variance in the second data set which is attributable to the individual signal
jnt_rank	integer for rank of the joint signal, i.e., number of joint components
equal.eig	logical (TRUE/FALSE) for whether components should contribute equal variance to signal matrices - default is FALSE
ind_rank1	integer for rank of the individual signal in first data set, i.e., number of joint components
ind_rank2	integer for rank of the individual signal in second data set, i.e., number of joint components
SVD.plots	logical (TRUE/FALSE) for whether plots of singular values from signal should be produced - used to confirm number of components
Error	logical (TRUE/FALSE) final data sets should be noise contaminated - default is FALSE; use TRUE to obtain pure signal datasets
print.cor	logical (TRUE/FALSE) for whether to print matrix of correlations between subject scores)

Value

A 'list' object which contains 1) list of signal matrices which additively comprise the simulated data sets, i.e. joint, individual, and error matrices for each data set; 2) list of simulated data sets (each equal to the sum of the matrices in part 1); 3) list of joint subject scores and individual subject scores for each data set, and 4) lsit of joint and individual loadings for each data set

Examples

ToyDat = GenerateToyData(n = 200, p1 = 2000, p2 = 1000, JntVarEx1 = 0.05, JntVarEx2 = 0.05,
                           IndVarEx1 = 0.25, IndVarEx2 = 0.25, jnt_rank = 1, equal.eig = FALSE,
                           ind_rank1 = 2, ind_rank2 = 3, SVD.plots = TRUE, Error = TRUE,
                           print.cor = TRUE)

CJIVE documentation built on Jan. 22, 2023, 1:24 a.m.