Bayesian Robust Estimation of the Mean

Wesley Johnson, Jessica Utts and Larry Pearson

Journal of the Royal Statistical Society Series C, 1986, vol. 35, issue 1, 63-72

Abstract: We indicate the applicability of a Bayesian method of estimating a mean in the face of mean‐shift contamination. Simple approximate Bayesian “confidence interval” formulas are obtained by approximating the posterior distribution. Several examples facilitate the comparison of the true and approximate posterior distributions. Performances of point estimators are assessed for the historical data sets presented by Stigler (1977). Empirical influence curves comparing the Bayesian estimators with other robust estimators are given. We conclude that the Bayesian estimators are competitive with some of the “best” robust estimators in the literature.

Date: 1986
References: Add references at CitEc
Citations:

Downloads: (external link)
https://doi.org/10.2307/2347866

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bla:jorssc:v:35:y:1986:i:1:p:63-72

Ordering information: This journal article can be ordered from
http://ordering.onli ... 1111/(ISSN)1467-9876

Access Statistics for this article

Journal of the Royal Statistical Society Series C is currently edited by R. Chandler and P. W. F. Smith

More articles in Journal of the Royal Statistical Society Series C from Royal Statistical Society Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().