Followed Jose's tips on inst/models, which is what caret uses. Remove…

…d the docs again to not expose these models to the user

RRegrs/R/RRegrs_Functions.R

@@ -1886,7 +1886,7 @@ Yrandom<- function(dss,trainFrac,best.reg,best.R2.ts,noYrand,ResBestF,rfe_SVM_pa
 # jseoane
 # use:
 # svmFuncsGradW: RAKOTOMAMONJY gradient w
-data(model.svmRadialReg)
+load(system.file("models", "model.svmRadialReg.RData", package = "RRegrs"))
 
 svmFuncsW = caretFuncs    ## regular ranking using w
 svmFuncsW$fit=function(x,y,first,last,...,tuneGrid){
@@ -2571,7 +2571,7 @@ ENETreg <- function(my.datf.train,my.datf.test,sCV,iSplit=1,fDet=F,outFile="") {
 
   #library(caret)
   #library(glmnet)
-  data(glmnetModel)
+  load(system.file("models", "glmnetModel.RData", package = "RRegrs"))
 
   net.c = my.datf.train[,1] # dependent variable is the first column in Training set
   RegrMethod <- "glmnet" # type of regression