R Under development (unstable) (2023-12-04 r85659 ucrt) -- "Unsuffered Consequences"
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> #source("charge.R")
> library("LINselect")
> 
> set.seed(15) # pour pouvoir comparer des exécutions sucessives
> ex <- simulData(p=25,n=25,r=0.5,rSN=10)
> 
> resVARselect <- VARselect(ex$Y,ex$X,exhaustive.dmax=4)
[1] "LASSO PROCEDURE with option max.steps= 25 dmax= 18"
[1] "ELASTIC-NET PROEDURE with options max.steps= 25 dmax= 18 en.lambda= 0.01 0.1 0.5 1 2 5"
[1] "RIDGE PROCEDURE with options dmax= 18 ridge.lambda= 0.01 0.1 0.5 1 2 5"
[1] "RANDOMFOREST PROCEDURE with option dmax= 18 rF.lmtry= 2"
[1] "PLS PROCEDURE with options dmax= 18 pls.ncomp= 1 2 3 4 5"
[1] "ADAPTIVE LASSO with WEIGHTS based on the RIDGE PROCEDURE"
[1] "with options max.steps= 25 dmax= 18 ALridge.lambda= 0.01 0.1 0.5 1 2 5"
[1] "ADAPTIVE LASSO  with WEIGHTS based on the PLS PROCEDURE"
[1] "with options max.steps= 25 dmax= 18 pls.ncomp= 1 2 3 4 5"
[1] "EXHAUSTIVE PROCEDURE"
[1] "dmax, the maximum number of selected variates equals 4"
[1] "selection of the best 1 variates"
[1] "the number of subsets of 1 variates among 25 equals 25"
[1] "selection of the best 2 variates"
[1] "the number of subsets of 2 variates among 25 equals 300"
[1] "selection of the best 3 variates"
[1] "the number of subsets of 3 variates among 25 equals 2300"
[1] "selection of the best 4 variates"
[1] "the number of subsets of 4 variates among 25 equals 12650"
> resVARselect$summary
$support
$support[[1]]
[1]  2  7 11 18


$crit
[1] 2258.512

$method
[1] "exhaustive"

> 
> resVARselect <-
+   VARselect(ex$Y,ex$X,normalize=FALSE,dmax=15,exhaustive.dmax=4,verbose=FALSE) 
> resVARselect$summary
$support
$support[[1]]
[1]  2  7 11 18


$crit
[1] 2258.512

$method
[1] "exhaustive"

> 
> ## Time consuming
> # X <- ex$X
> # X[,1] <- X[,1]/10
> # X[,2] <- X[,3]*10
> # resVARselect <- VARselect(ex$Y,X,dmax=20,exhaustive.dmax=2,verbose=FALSE)
> # resVARselect$summary
> 
> # resVARselect <- VARselect(ex$Y,X,normalize=FALSE,dmax=20,exhaustive.dmax=2,verbose=FALSE)
> # resVARselect$summary
> # 
> # resVARselect <- VARselect(ex$Y,ex$X,method="exhaustive",exhaustive.maxdim=5000)
> # resVARselect$summary
> # 
> # resVARselect <- VARselect(ex$Y,ex$X,method="en",en.lambda=5,dmax=20)
> # resVARselect$summary
> # 
> # set.seed(15)
> # ex <- simulData(p=100,n=100,r=0.5,rSN=10)
> # 
> # methodF=c("lasso","ridge","pls","en","ALridge","ALpls","rF")
> # resVARselect <- VARselect(ex$Y,ex$X,method=methodF)
> # resVARselect$summary
> # 
> # resVARselect <- VARselect(ex$Y,ex$X,method="rF",rF.lmtry=c(1,2,5))
> # resVARselect
> 
> # 
> # set.seed(15) 
> # ex <- simulData(p=100,n=50,r=0.95,rSN=10)
> # 
> # resVARselect <- VARselect(ex$Y,ex$X,method=methodF)
> # resVARselect$summary
> # 
> # set.seed(15)
> # ex <- simulData(p=1000,n=200,r=0.95,rSN=10)
> # methodF=c("lasso","ridge","pls","en","ALridge","ALpls")
> # resVARselect <- VARselect(ex$Y,ex$X,method=methodF,dmax=50,
> #                       en.lambda=c(0.01,1,5),
> #                       ridge.lambda=c(0.01,1,5),
> #                       ALridge.lambda=c(0.01,1,5))
> # resVARselect$summary
> # 
> # set.seed(15) 
> # p <- 5000 
> # n <- 100
> # X <-  matrix(rnorm(n*p),ncol=p,nrow=n)
> # Y <- rnorm(n)
> # resVARselect <- VARselect(Y,X,method="ALpls",ALpls.ncomp=4,dmax=50)
> # resVARselect
> 
> 
> 
> 
> 
> 
> 
> 
> proc.time()
   user  system elapsed 
   3.89    0.31    4.20