- return(tableauRecap)
-
- # modSel = capushe::capushe(tableauRecap, n)
- # indModSel <-
- # if (selecMod == 'DDSE')
- # as.numeric(modSel@DDSE@model)
- # else if (selecMod == 'Djump')
- # as.numeric(modSel@Djump@model)
- # else if (selecMod == 'BIC')
- # modSel@BIC_capushe$model
- # else if (selecMod == 'AIC')
- # modSel@AIC_capushe$model
- #
- # mod = as.character(tableauRecap[indModSel,1])
- # listMod = as.integer(unlist(strsplit(mod, "[.]")))
- # modelSel = models_list[[listMod[1]]][[listMod[2]]]
- #
- # ##Affectations
- # Gam = matrix(0, ncol = length(modelSel$pi), nrow = n)
- # for (i in 1:n){
- # for (r in 1:length(modelSel$pi)){
- # sqNorm2 = sum( (Y[i,]%*%modelSel$rho[,,r]-X[i,]%*%modelSel$phi[,,r])^2 )
- # Gam[i,r] = modelSel$pi[r] * exp(-0.5*sqNorm2)* det(modelSel$rho[,,r])
- # }
- # }
- # Gam = Gam/rowSums(Gam)
- # modelSel$affec = apply(Gam, 1,which.max)
- # modelSel$proba = Gam
- #
- # if (plot){
- # print(plot_valse(X,Y,modelSel,n))
- # }
- #
- # return(modelSel)
+ modSel = capushe::capushe(tableauRecap, n)
+ indModSel <-
+ if (selecMod == 'DDSE')
+ as.numeric(modSel@DDSE@model)
+ else if (selecMod == 'Djump')
+ as.numeric(modSel@Djump@model)
+ else if (selecMod == 'BIC')
+ modSel@BIC_capushe$model
+ else if (selecMod == 'AIC')
+ modSel@AIC_capushe$model
+
+ mod = as.character(tableauRecap[indModSel,1])
+ listMod = as.integer(unlist(strsplit(mod, "[.]")))
+ modelSel = models_list[[listMod[1]]][[listMod[2]]]
+
+ ##Affectations
+ Gam = matrix(0, ncol = length(modelSel$pi), nrow = n)
+ for (i in 1:n){
+ for (r in 1:length(modelSel$pi)){
+ sqNorm2 = sum( (Y[i,]%*%modelSel$rho[,,r]-X[i,]%*%modelSel$phi[,,r])^2 )
+ Gam[i,r] = modelSel$pi[r] * exp(-0.5*sqNorm2)* det(modelSel$rho[,,r])
+ }
+ }
+ Gam = Gam/rowSums(Gam)
+ modelSel$affec = apply(Gam, 1,which.max)
+ modelSel$proba = Gam
+
+ if (plot){
+ print(plot_valse(X,Y,modelSel,n))
+ }
+
+ return(modelSel)