Abstract
A method based on the prediction of order statistics is proposed to select the underlying parent distribution. A cross-validatory predictor and the best linear unbiased predictor are considered in choosing between gamma and Weibull models when shape parameters are only known to lie within a range. The proposed approach is evaluated using a large-scale Monte Carlo study. The results clearly show that the cross-validatory predictor performs well as a robust procedure in selecting between probability densities. Two well-known data sets are used to illustrate the procedure.
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