--- a
+++ b/allFunctions.R
@@ -0,0 +1,48 @@
+
+fitModel <- function(iter = 5, ...){
+    error = TRUE
+    i = 1
+    while ((error) && (i < 5)){
+        model <- try(train(...))
+        error <- class(model) == "try-error"
+        i = i + 1
+    }
+    if (i == iter) {
+        model = NA
+        warning("Algorithm did not converge. Returning NAs")
+    }
+    return(model)
+}
+
+predictModel <- function(model, newdata){
+    if (class(model) == "train"){
+        predicted = predict.train(model, newdata = newdata)    
+        ts.acc = sum(test.cond == as.numeric(predicted)) / length(test.cond)
+    }
+    if (class(model) != "train"){ 
+        ts.acc = NA
+    }
+    return(ts.acc)
+}
+
+
+foldIndex <- function(data, nSamp = NULL, nFolds = 5, repeats = 2){
+    if(is.null(nSamp)) n = nrow(data)
+    else n = nSamp
+    
+    indIn <- indOut <- list()
+    
+    for (j in 1:repeats){
+        tmpIn = createFolds(1:n, k = nFolds, list = TRUE, returnTrain = TRUE)
+        tmpOut = lapply(tmpIn, function(x)c(1:n)[-x])
+        
+        indIn = c(indIn, tmpIn)
+        indOut = c(indOut, tmpOut)
+    }
+    
+    nms = paste(rep(paste("Fold", 1:nFolds, sep = ""), repeats), 
+                rep(paste(".Rep", 1:repeats, sep = ""), c(rep(nFolds, repeats))), sep = "")
+    names(indIn) <- names(indOut) <- nms
+    return(list(indexIn = indIn, indexOut = indOut))
+}
+