Description Usage Arguments Value
This function applies Calc_fold_CV_Error over all folds of a cross validation. Use replicate if running multiple repetitions of cross-validation
1 2 | Evaluate_Tuning_Candidates(TRAIN, OutlierInd, cvfolds, parvec, ndsize,
ntreestune = 100, tol = 10^-4)
|
TRAIN |
matrix of training cases with response in last column |
OutlierInd |
Vector of zeros and ones indicating whether training cases came from contaminating distribution |
cvfolds |
number of folds to perform in cross validation |
parvec |
vector of candidate values for tuning parameter alpha |
ndsize |
nodesize random forest tuning parameter for cross validation |
ntreestune |
number of trees to use for forests involved in parameter tuning |
tol |
maximal change in interation for LOWESSRF weights in cross validation |
Returns array of dimensions 6 by 3 by length(parvec) by number of folds, containing errors. Dimensions index (1) type of error calculated 1-MSE without downweighting outliers in CV error 2-MAPE without downweighting outliers in CV error 3-MSE downweighting outliers according to BisqwtRF 4-MAPE downweighting outliers according to BisqwtRF 5-MSE downweighting outliers according to BisqwtRFL 6-MAPE downweighting outliers according to BisqwtRFL (2) applied to all cases in TRAIN2, outliers only, nonoutliers only (3) index of alpha from parvec (4) index of fold in cross validation
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