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Abstract:
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The goal of this dissertation is the construction of new goodness-of-fit tests,analysis of their properties, as well as to obtain new theoretical findings regarding the limitingdistributions of weakly degeneratedV−statistics with estimated parameters. New goodness-of-fit tests are based on equidistributional type characterizations of two sample functions.Test statistics are formed asL2distances betweenV−empirical distribution functions ofstatistics from characterization, and also asL2andL∞distances betweenV−empiricalLaplace transformations of those statistics. In the latter case, resulting test statistics can beobserved asV−statistics with an estimated parameter or as functions of those statistics.Until now, limiting results were known for non-degenerateV−statistics with estimatedparameters, as well as for weakly degenerateV−statistics of degree two with estimatedparameters. Limiting results for the appropriate class of weakly degenerateV−statistics withan estimated parameter of degreem, wheremis even number, are derived in this dissertation.Owing to these results, asymptotic properties for presented tests are determined. To assessthe quality of these tests, empirical powers were determined using Monte Carlo simulations, aswell as approximate Bahadur efficiency. New results are presented regarding the approximateBahadur efficiency in case of close alternatives, which is applicable also when the limitingdistribution of statistics under the null hypothesis is not normal. In this sense, the comparisonbetween many tests is performed, both classical tests and recently developed tests.All previously mentioned results were obtained for complete samples. Additional, modifi-cation of previously introduced tests for randomly censored data was also proposed. In sucha case, the new theoretically justified bootstrap method is proposed for the approximation ofp−value. |