This paper’s goal is to deal with the issue of hypothesis testing when the errors are assumed to be distributed according to a Generalized Error Distribution. Focus is given to the central tendency parameters, validating the suitability of nonparametric methods in this respect. The present work describes a simulation study aimed at assessing the validity of the Van der Waerden and Wilcoxon tests in the case of data coming from a G.E.D.; in order to compare the statistical power of such tests, we proceed to calculate the usual empirical significance level. The use of test statistics obtained by means of a Van der Waerden test generalized by considering the G.E.D.’s shape parameter provides better results, in terms of statistical power, compared to the Wilcoxon and the classic Van der Waerden tests
Statistical hypothesis testing within the Generalized Error Distribution: Comparing the behavior of some nonparametric techniques
Massimiliano Giacalone;
2020
Abstract
This paper’s goal is to deal with the issue of hypothesis testing when the errors are assumed to be distributed according to a Generalized Error Distribution. Focus is given to the central tendency parameters, validating the suitability of nonparametric methods in this respect. The present work describes a simulation study aimed at assessing the validity of the Van der Waerden and Wilcoxon tests in the case of data coming from a G.E.D.; in order to compare the statistical power of such tests, we proceed to calculate the usual empirical significance level. The use of test statistics obtained by means of a Van der Waerden test generalized by considering the G.E.D.’s shape parameter provides better results, in terms of statistical power, compared to the Wilcoxon and the classic Van der Waerden testsI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
