A note on the convergence rates for empirical Bayes estimators of parameters in multiple-parameter exponential families

Shunpu Zhang, Laisheng Wei

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Under suitable conditions upon prior distribution, the convergence rates for empirical Bayes estimators of parameters in multi-parameter exponential families (M-PEF) are obtained. It is shown that the assumptions Tong (1996) imposed on the marginal density can be reduced. The above result can also be extended to more general forms of M-PEF. Finally, some examples which satisfy the conditions of the theorems are given.

Original languageEnglish (US)
Pages (from-to)1273-1291
Number of pages19
JournalCommunications in Statistics - Theory and Methods
Volume28
Issue number6
DOIs
StatePublished - Jan 1 1999

Fingerprint

Empirical Bayes Estimator
Exponential Family
Convergence Rate
Prior distribution
Theorem

Keywords

  • A note
  • Convergence rates
  • Empirical Bayes estimation
  • Kernel estimation
  • Multi-parameter exponential family

ASJC Scopus subject areas

  • Statistics and Probability

Cite this

A note on the convergence rates for empirical Bayes estimators of parameters in multiple-parameter exponential families. / Zhang, Shunpu; Wei, Laisheng.

In: Communications in Statistics - Theory and Methods, Vol. 28, No. 6, 01.01.1999, p. 1273-1291.

Research output: Contribution to journalArticle

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