ecm_fa: Estimates the parameters of study-specific FA models
In rdevito/MSFA: Maximum Likelihood Estimation and Bayesian analysis of MSFA models

Description Usage Arguments Value References

Maximum likelihood estimation of study-specific FA models parameters via the ECM algorithm, adopting the upper-triangular zero constraint to achieve identification for each loading matrix. Note: the function can also estimate a FA model for a single study, by specifiyng X_s = list(data), where data is the data matrix.

ecm_fa(
  X_s,
  tot_s,
  nIt = 50000,
  tol = 10^-7,
  block_lower = TRUE,
  robust = FALSE,
  corr = TRUE,
  mcd = FALSE,
  trace = TRUE,
  traceIT = 1000
)

`X_s`	List of lenght S, corresponding to number of different studies considered. Each element of the list contains a data matrix, with the same number of columns P for all the studies.
`tot_s`	Number of latent factors for each study. A vector of positive integers of length S.
`nIt`	Maximum number of iterations for the ECM algorithm. Default is 50000.
`tol`	Tolerance for declaring convergence of the ECM algorithm. Default is 10^-7.
`block_lower`	Should the upper-triangular zero constraint be enforced? Default is `TRUE` (strongly suggested).
`robust`	If `TRUE`, robust covariance matrix is used in place of the sample covariance. Default is `FALSE`.
`corr`	If `TRUE`, the analysis will employ the correlation matrix instead of the covariance matrix.
`mcd`	If `TRUE`, the robust estimator used for the covariance is the same proposed in Pison et al. (2003), otherwise the default value of the function `CovRob` of the `robust` library is employed. Default is `FALSE`.
`trace`	If `TRUE` then trace information is being printed every `traceIT` iterations of the ECM algorithm.
`traceIT`	Frequency of tracing information.

A list containing the following components:

`Omega_s, Psi_s`	the estimated model matrices.
`loglik`	the value of the log likelihood function at the final estimates.
`AIC, BIC`	model selection criteria at the estimate.
`npar`	number of model parameters.
`iter`	the number of ECM iterations performed.