Remove arg n in plot_valse (deduce from X)
[valse.git] / pkg / R / computeGridLambda.R
1 #' computeGridLambda
2 #'
3 #' Construct the data-driven grid for the regularization parameters used for the Lasso estimator
4 #'
5 #' @param phiInit value for phi
6 #' @param rhoInit for rho
7 #' @param piInit for pi
8 #' @param gamInit value for gamma
9 #' @param X matrix of covariates (of size n*p)
10 #' @param Y matrix of responses (of size n*m)
11 #' @param gamma power of weights in the penalty
12 #' @param mini minimum number of iterations in EM algorithm
13 #' @param maxi maximum number of iterations in EM algorithm
14 #' @param eps threshold to stop EM algorithm
15 #' @param fast boolean to enable or not the C function call
16 #'
17 #' @return the grid of regularization parameters
18 #'
19 #' @export
20 computeGridLambda <- function(phiInit, rhoInit, piInit, gamInit, X, Y, gamma, mini,
21 maxi, eps, fast)
22 {
23 n <- nrow(X)
24 p <- ncol(X)
25 m <- ncol(Y)
26 k <- length(piInit)
27
28 list_EMG <- EMGLLF(phiInit, rhoInit, piInit, gamInit, mini, maxi, gamma, lambda = 0,
29 X, Y, eps, fast)
30
31 grid <- array(0, dim = c(p, m, k))
32 for (j in 1:p)
33 {
34 for (mm in 1:m)
35 grid[j, mm, ] <- abs(list_EMG$S[j, mm, ])/(n * list_EMG$pi^gamma)
36 }
37 sort(unique(grid))
38 }