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Testing a point null hypothesis: the comparison of p-values and Bayesian evidence in multivariate normal distribution.
Author(s):
1. Rahim Chinipardaz: Department of Statistics, University of Shahid Charman, Ahvaz, Iran
2. Asieb Abtahi: Department of Statistics, University of Shahid Charman, Ahvaz, Iran
Abstract:
Testing of point null hypothesis on the mean vector of a multivariate normal distribution is studied. Of interest is relationship between p-value (or observed significance level) and Bayesian measure of evidence against the null hypothesis, expressed in terms of the infimum of the posterior probability of the null hypothesis. When the dimension of the parameter space is one, the p-value is much smaller than the Bayesian evidence. For dimension greater than one the p-value is typically larger than the Bayesian evidence. If the symmetric class of priors were used, like the uninvariate distribution, the Bayesian evidence is much larger than the corresponding p-value and remains constant for large dimension of parameter. This means that p-values and Bayesian evidence are irreconcilable. At the end of this paper, calibration of p-value given by Sellke et al (2001) was adapted to multivariate case for creating reconcilability between two methods.
Page(s): 123-133
DOI: DOI not available
Published: Journal: Pakistan Journal of Statistics, Volume: 24, Issue: 2, Year: 2008
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