An adaptive estimator of location based on the t-family

D. L. Hawkins, C. K. Lakshminarayan

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

For estimating the location of a continuous symmetric distribution, we consider the maximum likelihood estimate of location in a location-scale-tailweight family based on the t-distributions. The idea is to obtain an asymptotically efficient estimator of location within a parametric family large enough to contain members close to the normal tailweight, as well as members with heavy tails. This is the “partially adaptive” idea of Bickel (1982). Ve present Monte Carlo results comparing this estimator to several competitors, particularly with one due to Hogg which motivated our idea.

Original languageEnglish
Pages (from-to)747-761
Number of pages15
JournalCommunications in Statistics - Theory and Methods
Volume23
Issue number3
DOIs
StatePublished - 1 Jan 1994

Keywords

  • maximum likelihood
  • partially adaptive
  • symmetric distributions
  • tailweight

Fingerprint

Dive into the research topics of 'An adaptive estimator of location based on the t-family'. Together they form a unique fingerprint.

Cite this