#' #TODO: a few examples
#' @export
valse = function(X, Y, procedure='LassoMLE', selecMod='DDSE', gamma=1, mini=10, maxi=50,
- eps=1e-4, kmin=2, kmax=2, rang.min=1, rang.max=10, ncores_outer=1, ncores_inner=3,
+ eps=1e-4, kmin=2, kmax=4, rang.min=1, rang.max=10, ncores_outer=1, ncores_inner=1, size_coll_mod = 50,
verbose=FALSE)
{
p = dim(X)[2]
grid_lambda <- computeGridLambda(P$phiInit, P$rhoInit, P$piInit, P$gamInit, X, Y,
gamma, mini, maxi, eps)
# TODO: 100 = magic number
- if (length(grid_lambda)>100)
- grid_lambda = grid_lambda[seq(1, length(grid_lambda), length.out = 100)]
+ if (length(grid_lambda)>size_coll_mod)
+ grid_lambda = grid_lambda[seq(1, length(grid_lambda), length.out = size_coll_mod)]
if (verbose)
print("Compute relevant parameters")
#from the grid: S$selected corresponding to selected variables
S = selectVariables(P$phiInit, P$rhoInit, P$piInit, P$gamInit, mini, maxi, gamma,
grid_lambda, X, Y, 1e-8, eps, ncores_inner) #TODO: 1e-8 as arg?! eps?
-
+
if (procedure == 'LassoMLE')
{
if (verbose)
print('run the procedure Lasso-MLE')
#compute parameter estimations, with the Maximum Likelihood
#Estimator, restricted on selected variables.
- models <- constructionModelesLassoMLE(phiInit, rhoInit, piInit, gamInit, mini,
- maxi, gamma, X, Y, thresh, eps, S$selected, ncores_inner, verbose)
+ models <- constructionModelesLassoMLE(P$phiInit, P$rhoInit, P$piInit, P$gamInit, mini,
+ maxi, gamma, X, Y, thresh, eps, S, ncores_inner, artefact = 1e3, verbose)
}
else
{
# List (index k) of lists (index lambda) of models
models_list <-
- if (ncores_k > 1)
+ if (ncores_outer > 1)
parLapply(cl, kmin:kmax, computeModels)
else
lapply(kmin:kmax, computeModels)
- if (ncores_k > 1)
+ if (ncores_outer > 1)
parallel::stopCluster(cl)
if (! requireNamespace("capushe", quietly=TRUE))
}
# Get summary "tableauRecap" from models ; TODO: jusqu'à ligne 114 à mon avis là c'est faux :/
- tableauRecap = t( sapply( models_list, function(models) {
- llh = do.call(rbind, lapply(models, function(model) model$llh)
+ tableauRecap = sapply( models_list, function(models) {
+ llh = do.call(rbind, lapply(models, function(model) model$llh))
LLH = llh[-1,1]
D = llh[-1,2]
- c(LLH, D, rep(k, length(model)), 1:length(model))
- ) } ) )
+ c(LLH, D, rep(k, length(LLH)), 1:length(LLH))
+ })
+ tableauRecap
if (verbose)
print('Model selection')
tableauRecap = tableauRecap[rowSums(tableauRecap[, 2:4])!=0,]
modSel@BIC_capushe$model
else if (selecMod == 'AIC')
modSel@AIC_capushe$model
- model[[tableauRecap[indModSel,3]]][[tableauRecap[indModSel,4]]]
+ models_list[[tableauRecap[indModSel,3]]][[tableauRecap[indModSel,4]]]
}