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[valse.git] / R / gridLambda.R
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d1531659 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#-----------------------------------------------------------------------
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12gridLambda = function(phiInit, rhoInit, piInit, gamInit, X, Y, gamma, mini, maxi, tau)
13{
d1531659 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",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)
39046da6 31}