Open Access Open Access  Restricted Access Subscription or Fee Access

Empirical bayes analysis for the parameter of truncation distribution under Ø-mixing Samples

Juan Huang

Abstract


In this paper, by using the kernel-type density estimation , the empirical Bayes test rule for the continuous one-parameter exponential family is constructed under Ø-mixing samples. The asymptotically optimal property and convergence rates for the proposed EB test are obtained under suitable conditions.

Keywords


Ø-mixing samples, kernel estimation of density function, empirical Bayes test, asymptotic optimality,convergence rates.

Full Text:

PDF


Disclaimer/Regarding indexing issue:

We have provided the online access of all issues and papers to the indexing agencies (as given on journal web site). It’s depend on indexing agencies when, how and what manner they can index or not. Hence, we like to inform that on the basis of earlier indexing, we can’t predict the today or future indexing policy of third party (i.e. indexing agencies) as they have right to discontinue any journal at any time without prior information to the journal. So, please neither sends any question nor expects any answer from us on the behalf of third party i.e. indexing agencies.Hence, we will not issue any certificate or letter for indexing issue. Our role is just to provide the online access to them. So we do properly this and one can visit indexing agencies website to get the authentic information. Also: DOI is paid service which provided by a third party. We never mentioned that we go for this for our any journal. However, journal have no objection if author go directly for this paid DOI service.