A paradox concerning shrinkage estimators: Should a known scale parameter be replaced by an estimated value in the shrinkage factor?

Dominique Fourdrinier, William E. Strawderman

Research output: Contribution to journalArticlepeer-review

22 Scopus citations

Abstract

When estimating, under quadratic loss, the location parameter θ of a spherically symmetric distribution with known scale parameter, we show that it may be that the common practice of utilizing the residual vector as an estimate of the variance is preferable to using the known value of the variance. In the context of Stein-like shrinkage estimators, we exhibit sufficient conditions on the spherical distributions for which this paradox occurs. In particular, we show that it occurs for t-distributions when the dimension of the residual vector is sufficiently large. The main tools in the development are upper and lower bounds on the risks of the James-Stein estimators which are exact at θ= 0.

Original languageEnglish (US)
Pages (from-to)109-140
Number of pages32
JournalJournal of Multivariate Analysis
Volume59
Issue number2
DOIs
StatePublished - Nov 1996

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Numerical Analysis
  • Statistics, Probability and Uncertainty

Keywords

  • James-stein estimation
  • Location parameter
  • Minimaxity
  • Quadratic loss
  • Robustness
  • Spherical symmetry

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