A new Bayesian procedure for testing point null hypotheses

Autor:	Yuliang Yin
Rok vydání:	2011
Předmět:	Statistics and Probability Bayesian statistics Computational Mathematics Frequentist inference Econometrics Null distribution Bayes factor p-value Statistics Probability and Uncertainty Bayesian linear regression Bayesian inference Bayesian average Mathematics
Zdroj:	Computational Statistics. 27:237-249
ISSN:	1613-9658 0943-4062
DOI:	10.1007/s00180-011-0252-6
Popis:	Testing point null hypotheses is a very common activity in various applied situations. However, the existing Bayesian testing procedure may give evidence which does not agree with the classical frequentist p-value in many point null testing situations. A typical example for this is the well known Lindley’s paradox (Lindley in Biometrika 44:187–192, 1957). In this paper we propose an alternative testing procedure in the Bayesian framework. It is shown that for many classical testing examples, the Bayesian evidence derived by our new testing procedure is not contradictory to its frequentist counterpart any more. In fact, the new Bayesian evidence under the noninformative prior is usually coincident with the frequentist observed significance level.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::ce14b02b5ba495c087866b612bebf7b7 https://doi.org/10.1007/s00180-011-0252-6 Zobrazit plný text záznamu Full text from SpringerLink