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[valse.git] / R / gridLambda.R

#' Construct the data-driven grid for the regularization parameters used for the Lasso estimator
#' @param phiInit value for phi
#' @param rhoInt  value for rho
#' @param piInit  value for pi
#' @param gamInit value for gamma
#' @param mini    minimum number of iterations in EM algorithm
#' @param maxi    maximum number of iterations in EM algorithm
#' @param tau    threshold to stop EM algorithm
#' @return the grid of regularization parameters
#' @export
#-----------------------------------------------------------------------
gridLambda = function(phiInit, rhoInit, piInit, gamInit, X, Y, gamma, mini, maxi, tau)
{
  n = nrow(X)
  p = dim(phiInit)[1]
  m = dim(phiInit)[2]
  k = dim(phiInit)[3]
  
  list_EMG = .Call("EMGLLF",phiInit,rhoInit,piInit,gamInit,mini,maxi,1,0,X,Y,tau)
  
  grid = array(0, dim=c(p,m,k))
  for (i in 1:p)
  {
    for (j in 1:m)
      grid[i,j,] = abs(list_EMG$S[i,j,]) / (n*list_EMG$pi^gamma)
  }
  grid = unique(grid)
  grid = grid[grid <=1]
  
  return(grid)
}