Kolmogorov-smirnov and continuous ranked probability score validation on the Bayesian model averaging for microarray data

The Bayesian Model Averaging (BMA) required the validation step to determine the accuracy of BMA model. Kolmogorov-Smirnov (KS) and Continuous Ranked Probability Score (CRPS) are used to validate the BMA model. The absolute difference between the empirical cumulative distribution and the hypothesis cumulative distribution were the basic idea of these methods. The KS method uses the distance concept and CRPS method uses the area concept. The validation of BMA model on microarray data by KS and CRPS methods would be identified in this paper. The results have succeed to indentify the performance of KS and CRPS in the validation to BMA model on microarray data with an average value of KS=0.469 and CRPS=0.211 for n=10 and then the value of KS=0.403 and CRPS=0.11 for n=12.