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Fit the high-dimensional multi-study elliptical factor model

Source: R/main.R
MultiEFM.Rd

Fit the high-dimensional multi-study elliptical factor model which learns latent features and accounts for the heterogeneity among sources.

Usage

MultiEFM(
  XList,
  q,
  qs_vec,
  loads_method = c("Residual", "Ortho"),
  fac_est_method = c("Huber", "LS"),
  n_threads = 4,
  sample_pairs = 0,
  epsObj = 1e-06,
  maxIter = 20,
  verbose = TRUE,
  seed = 1
)

Arguments

XList

A length-S list, where each component represents a data matrix for a specific study.

q

an integer, specify the number of study-shared factors.

qs_vec

an integer vector with length S, specify the number of study-specified factors for each study.

loads_method

a character string specifying the method for loading estimation. Options are "Residual" or "Ortho".

fac_est_method

a character string specifying the method for factor estimation. Options are "Huber" or "LS" (Least Squares).

n_threads

an integer, specify the number of threads for parallel computing; default as 4.

sample_pairs

an integer, specify the number of sample pairs used for estimation; default as 0.

epsObj

a positive value, tolerance for convergence, default as 1e-6.

maxIter

the maximum iteration of the algorithm. The default is 20.

verbose

a logical value, whether to output the information in iteration.

seed

an integer, specify the random seed for reproducibility in initialization; default as 1.

Value

return a list including the following components:

A

the estimated loading matrix corresponding to study-shared factors;

F

a list composed by the estimation of study-shared factor matrix for each study;

B

a list composed by the loading matrices corresponding to the study-specified factors;

H

a list composed by the estimation of study-specified factor matrix for each study.

Examples

if (FALSE) { # \dontrun{
p <- 100
nvec <- c(150, 200)
qs <- c(2, 2)
datList <- gendata_simu_robust(seed=1, nvec=nvec, p=p, q=3, qs=qs, rho=c(5,5),
                               err.type='mvt', sigma2_eps = 1, nu=3)
XList <- datList$Xlist
res <- MultiEFM(XList, q=3, qs_vec=qs)
str(res)
} # }