Estimating ordered location and scale parameters

D. Kushary, A. Cohen

Research output: Contribution to journalArticlepeer-review

32 Scopus citations

Abstract

Assume independent random samples are drawn from K populations whose distributions are location, scale, or location-scale families. Let T1 be an estimator which is admissible for the parameter corresponding to the first population. Next assume that the parameters are ordered. The question addressed is does T1 remain admissible? For various special cases of the model we exhibit estimators which are better than T1. The models include estimating a location parameter with squared error loss, estimating a scale parameter with normalized squared error loss, finding a confidence interval for a location parameter, and finding a confidence interval for a normal variance. In these latter models universal domination as defined by Hwang [4] is shown.

Original languageEnglish (US)
Pages (from-to)201-214
Number of pages14
JournalStatistics and Risk Modeling
Volume7
Issue number3
DOIs
StatePublished - Mar 1989
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Modeling and Simulation
  • Statistics, Probability and Uncertainty

Keywords

  • Location parameters
  • admissibility
  • confidence intervals
  • ordered parameters
  • scale parameters
  • universal domination

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