R/gridLambda.R

   1 #' Construct the data-driven grid for the regularization parameters used for the Lasso estimator
   2 #' @param phiInit value for phi
   3 #' @param rhoInt    value for rho
   4 #' @param piInit    value for pi
   5 #' @param gamInit value for gamma
   6 #' @param mini      minimum number of iterations in EM algorithm
   7 #' @param maxi      maximum number of iterations in EM algorithm
   8 #' @param tau       threshold to stop EM algorithm
   9 #' @return the grid of regularization parameters
  10 #' @export
  11 #-----------------------------------------------------------------------
  12 gridLambda = function(phiInit, rhoInit, piInit, gamInit, X, Y, gamma, mini, maxi, tau)
  13 {
  14     n = nrow(X)
  15     p = dim(phiInit)[1]
  16     m = dim(phiInit)[2]
  17     k = dim(phiInit)[3]
  18
  19     list_EMG = .Call("EMGLLF_core",phiInit,rhoInit,piInit,gamInit,mini,maxi,1,0,X,Y,tau)
  20
  21     grid = array(0, dim=c(p,m,k))
  22     for (i in 1:p)
  23     {
  24         for (j in 1:m)
  25             grid[i,j,] = abs(list_EMG$S[i,j,]) / (n*list_EMG$pi^gamma)
  26     }
  27     grid = unique(grid)
  28     grid = grid[grid <=1]
  29
  30     return(grid)
  31 }