#'
#' @param phiInit an initial estimator for phi (size: p*m*k)
#' @param rhoInit an initial estimator for rho (size: m*m*k)
-#' @param piInit\tan initial estimator for pi (size : k)
+#' @param piInit an initial estimator for pi (size : k)
#' @param gamInit an initial estimator for gamma
-#' @param mini\t\tminimum number of iterations in EM algorithm
-#' @param maxi\t\tmaximum number of iterations in EM algorithm
-#' @param gamma\t power in the penalty
+#' @param mini minimum number of iterations in EM algorithm
+#' @param maxi maximum number of iterations in EM algorithm
+#' @param gamma power in the penalty
#' @param glambda grid of regularization parameters
-#' @param X\t\t\t matrix of regressors
-#' @param Y\t\t\t matrix of responses
+#' @param X matrix of regressors
+#' @param Y matrix of responses
#' @param thresh real, threshold to say a variable is relevant, by default = 1e-8
-#' @param eps\t\t threshold to say that EM algorithm has converged
+#' @param eps threshold to say that EM algorithm has converged
#' @param ncores Number or cores for parallel execution (1 to disable)
#'
#' @return a list of outputs, for each lambda in grid: selected,Rho,Pi
params <- EMGLLF(phiInit, rhoInit, piInit, gamInit, mini, maxi, gamma, lambda,
X, Y, eps, fast)
- p <- dim(phiInit)[1]
- m <- dim(phiInit)[2]
+ p <- ncol(X)
+ m <- ncol(Y)
# selectedVariables: list where element j contains vector of selected variables
# in [1,m]
selectedVariables <- lapply(1:p, function(j) {
# from boolean matrix mxk of selected variables obtain the corresponding boolean
# m-vector, and finally return the corresponding indices
- seq_len(m)[apply(abs(params$phi[j, , ]) > thresh, 1, any)]
+ if (m>1) {
+ seq_len(m)[apply(abs(params$phi[j, , ]) > thresh, 1, any)]
+ } else {
+ if (any(params$phi[j, , ] > thresh))
+ 1
+ else
+ numeric(0)
+ }
})
list(selected = selectedVariables, Rho = params$rho, Pi = params$pi)
}
if (ncores > 1)
parallel::stopCluster(cl)
+
+ print(out)
# Suppress models which are computed twice En fait, ca ca fait la comparaison de
# tous les parametres On veut juste supprimer ceux qui ont les memes variables
# sélectionnées