R/RcppExports.R

In dcgerard/vicar: Various Ideas for Confounder Adjustment in Regression

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#' Fast Gibbs sampler for Bayesian factor analysis.
#'
#'
#'
#' @param Y22init A matrix of numerics. The initial value of Y22.
#' @param Y21 A matrix of numerics.
#' @param Y31 A matrix of numerics.
#' @param Y32 A matrix of numerics.
#' @param nsamp The number of iterations to run in the Gibbs sampler, not including the burnin.
#' @param burnin The number of iterations to burnin.
#' @param thin We only collect samples every \code{thin} iterations.
#' @param Linit A numeric matrix. The initial values of the loadings.
#' @param Finit A numeric matrix. The initial values for the factors.
#' @param xi_init A numeric vector. The initial values of the precisions.
#' @param phi_init A numeric scalar. The initial value of the mean of the precisions.
#' @param zeta_init A numeric vector. The initial values of the augmented row precisions.
#' @param theta_init A numeric vector. The initial values the the factor precisions.
#' @param kappa_init A numeric scalar. The initial value of the mean of the factor precisions.
#' @param rho_0 The prior sample size for column-specific the
#'     precisions.
#' @param alpha_0 The prior sample size for the mean of the
#'     column-specific precisions.
#' @param beta_0 The prior mean of the mean of the column-specific
#'     precisions.
#' @param eta_0 The prior sample size of the expanded parameters.
#' @param tau_0 The prior mean of of the expanded parameters.
#' @param delta_0 The prior sample size of the column-specific
#'     precisions of the factors.
#' @param lambda_0 The prior sample size of the mean of the
#'     column-specific precisions of the factors.
#' @param nu_0 The prior mean of the mean of the column-specific
#'     precisions of the factors.
#' @param hetero_factors A logical. Should we also update the precisions of the
#'     factors (\code{TRUE}), or not (\code{FALSE})?
#' @param display_progress A logical. If \code{TRUE}, then a progress bar will
#'     be displayed and you'll be able to interrupt the C++ code. If \code{FALSE},
#'     then neither of these capabilities will be provided.
#'
#' @author David Gerard
#' @export
#'
#'
bfa_gd_gibbs <- function(Linit, Finit, xi_init, phi_init, zeta_init, theta_init, kappa_init, Y22init, Y21, Y31, Y32, nsamp, burnin, thin, rho_0, alpha_0, delta_0, lambda_0, nu_0, beta_0, eta_0, tau_0, hetero_factors, display_progress) {
    .Call('_vicar_bfa_gd_gibbs', PACKAGE = 'vicar', Linit, Finit, xi_init, phi_init, zeta_init, theta_init, kappa_init, Y22init, Y21, Y31, Y32, nsamp, burnin, thin, rho_0, alpha_0, delta_0, lambda_0, nu_0, beta_0, eta_0, tau_0, hetero_factors, display_progress)
}

#' Fast Gibbs sampler for Bayesian factor analysis.
#'
#' This is very similar to \code{\link{bfa_gd_gibbs}} except that we link the precisions
#' of the observations with the precisions of the factors. For some reason, this works
#' very well in practice.
#'
#'
#'
#'
#'
#'
#' @param Y22init A matrix of numerics. The initial value of Y22.
#' @param Y21 A matrix of numerics.
#' @param Y31 A matrix of numerics.
#' @param Y32 A matrix of numerics.
#' @param nsamp The number of iterations to run in the Gibbs sampler, not including the burnin.
#' @param burnin The number of iterations to burnin.
#' @param thin We only collect samples every \code{thin} iterations.
#' @param Linit A numeric matrix. The initial values of the loadings.
#' @param Finit A numeric matrix. The initial values for the factors.
#' @param xi_init A numeric vector. The initial values of the precisions.
#' @param phi_init A numeric scalar. The initial value of the mean of the precisions.
#' @param zeta_init A numeric vector. The initial values of the augmented row precisions.
#' @param rho_0 The prior sample size for column-specific the
#'     precisions.
#' @param alpha_0 The prior sample size for the mean of the
#'     column-specific precisions.
#' @param beta_0 The prior mean of the mean of the column-specific
#'     precisions.
#' @param eta_0 The prior sample size of the expanded parameters.
#' @param tau_0 The prior mean of of the expanded parameters.
#' @param display_progress A logical. If \code{TRUE}, then a progress bar will
#'     be displayed and you'll be able to interrupt the C++ code. If \code{FALSE},
#'     then neither of these capabilities will be provided.
#'
#' @author David Gerard
#' @export
#'
#'
bfa_gs_linked_gibbs <- function(Linit, Finit, xi_init, phi_init, zeta_init, Y22init, Y21, Y31, Y32, nsamp, burnin, thin, rho_0, alpha_0, beta_0, eta_0, tau_0, display_progress) {
    .Call('_vicar_bfa_gs_linked_gibbs', PACKAGE = 'vicar', Linit, Finit, xi_init, phi_init, zeta_init, Y22init, Y21, Y31, Y32, nsamp, burnin, thin, rho_0, alpha_0, beta_0, eta_0, tau_0, display_progress)
}