fix few things
[valse.git] / pkg / R / constructionModelesLassoMLE.R
... / ...
CommitLineData
1#' constructionModelesLassoMLE
2#'
3#' Construct a collection of models with the Lasso-MLE procedure.
4#'
5#'
6#' @param ...
7#'
8#' @return ...
9#'
10#' export
11constructionModelesLassoMLE = function(phiInit, rhoInit, piInit, gamInit, mini, maxi,
12 gamma, X, Y, thresh, tau, S, ncores=3, fast=TRUE, verbose=FALSE)
13{
14 if (ncores > 1)
15 {
16 cl = parallel::makeCluster(ncores, outfile='')
17 parallel::clusterExport( cl, envir=environment(),
18 varlist=c("phiInit","rhoInit","gamInit","mini","maxi","gamma","X","Y","thresh",
19 "tau","S","ncores","verbose") )
20 }
21
22 # Individual model computation
23 computeAtLambda <- function(lambda)
24 {
25 if (ncores > 1)
26 require("valse") #nodes start with an empty environment
27
28 if (verbose)
29 print(paste("Computations for lambda=",lambda))
30
31 n = dim(X)[1]
32 p = dim(phiInit)[1]
33 m = dim(phiInit)[2]
34 k = dim(phiInit)[3]
35 sel.lambda = S[[lambda]]$selected
36# col.sel = which(colSums(sel.lambda)!=0) #if boolean matrix
37 col.sel <- which( sapply(sel.lambda,length) > 0 ) #if list of selected vars
38 if (length(col.sel) == 0)
39 return (NULL)
40
41 # lambda == 0 because we compute the EMV: no penalization here
42 res = EMGLLF(phiInit[col.sel,,],rhoInit,piInit,gamInit,mini,maxi,gamma,0,
43 X[,col.sel], Y, tau, fast)
44
45 # Eval dimension from the result + selected
46 phiLambda2 = res$phi
47 rhoLambda = res$rho
48 piLambda = res$pi
49 phiLambda = array(0, dim = c(p,m,k))
50 for (j in seq_along(col.sel))
51 phiLambda[col.sel[j],sel.lambda[[j]],] = phiLambda2[j,sel.lambda[[j]],]
52 dimension = length(unlist(sel.lambda))
53
54 # Computation of the loglikelihood
55 densite = vector("double",n)
56 for (r in 1:k)
57 {
58 if (length(col.sel)==1){
59 delta = (Y%*%rhoLambda[,,r] - (X[, col.sel]%*%t(phiLambda[col.sel,,r])))
60 } else delta = (Y%*%rhoLambda[,,r] - (X[, col.sel]%*%phiLambda[col.sel,,r]))
61 densite = densite + piLambda[r] *
62 det(rhoLambda[,,r])/(sqrt(2*base::pi))^m * exp(-diag(tcrossprod(delta))/2.0)
63 }
64 llhLambda = c( sum(log(densite)), (dimension+m+1)*k-1 )
65 list("phi"= phiLambda, "rho"= rhoLambda, "pi"= piLambda, "llh" = llhLambda)
66 }
67
68 # For each lambda, computation of the parameters
69 out =
70 if (ncores > 1)
71 parLapply(cl, 1:length(S), computeAtLambda)
72 else
73 lapply(1:length(S), computeAtLambda)
74
75 if (ncores > 1)
76 parallel::stopCluster(cl)
77
78 out
79}