diff --git a/src/convenience.jl b/src/convenience.jl
index 566dbca..346146d 100644
--- a/src/convenience.jl
+++ b/src/convenience.jl
@@ -16,62 +16,6 @@ XVal             = my_split["XVal"];
 using Random
 
 
-"""
-    calculateRMSECV(X, y, regfunction, funcargs, n_splits=1, n_folds=5, rngseed=42, emscpreproc=false, emscdegree=6)
-    calculateRMSECV(X, y, splits, regfunction, funcargs, emscpreproc=false, emscdegree=6)
-
-Calculates RMSECV.
-Second function calculates RMSECV according to data split given by variable 'split' (which should be output of
-function computeCVSplitInds).
-
-Returns meanrmsecv, rmsecv where rmsecv is kmax x n_splits matrix, and meanrmsecv is vector of length kmax.
-"""
-function calculateRMSECV(X, y, regfunction, funcargs, n_splits=1, n_folds=5, rngseed=42, emscpreproc=false, emscdegree=6)
-
-splits         = createCVSplitInds(X, n_splits, n_folds, rngseed);
-meanrmse, rmse = calculateRMSECV(X, y, splits, regfunction, funcargs, emscpreproc, emscdegree);
-    
-return meanrmsecv, rmsecv
-end
-
-function calculateRMSECV(X, y, splits, regfunction, funcargs, emscpreproc=false, emscdegree=6)
-
-n_splits = size(splits,2);
-B, _     = regfunction(X, y, funcargs...); # <- Slow, but works in general. Maybe add some special cases for known functions?
-    println("her")
-kmax     = size(B, 2);
-rmsecv   = zeros(kmax, nsplits);
-n_folds  = length(unique(splits[:,1]))
-    
-for i in 1:n_splits
-    
-    for j=1:n_folds
-            XTrain = X[splits[:,j] .!= j,:];
-            XTest  = X[splits[:,j] .== j,:];
-            yTrain = y[splits[:,j] .!= j,:];
-            yTest  = y[splits[:,j] .== j,:];
-        
-        if emscpreproc
-            XTrain, output = EMSC(XTrain, emscdegree, "svd", 1, -1, 0); # nRef, baseDeg, intF
-            XTest, _       = EMSC(XTest, output["model"]);
-        end
-
-        B, _   = regfunction(XTrain, yTrain, funcargs...);
-
-        for k=1:kmax
-            yTestPred, _  = predRegression(XTest, B[:,k], yTest);
-            rmsecv[k, i] += sum((yTestPred - yTest).^2);
-        end
-    end
-
-end
-
-rmsecv     = sqrt.(rmsecv ./ n);
-meanrmsecv = mean(rmsecv, dims=2);
-
-return meanrmsecv, rmsecv
-end
-
 
 """
     function createCVSplitInds(X, n_splits=1, n_folds=5, rngseed=42)