4.6 Article

OPTIMAL SHRINKAGE ESTIMATION OF MEAN PARAMETERS IN FAMILY OF DISTRIBUTIONS WITH QUADRATIC VARIANCE

Journal

ANNALS OF STATISTICS
Volume 44, Issue 2, Pages 564-597

Publisher

INST MATHEMATICAL STATISTICS
DOI: 10.1214/15-AOS1377

Keywords

Hierarchical model; shrinkage estimator; unbiased estimate of risk; asymptotic optimality; quadratic variance function; NEF-QVF; location-scale family

Funding

  1. NIH
  2. NSF
  3. Division Of Mathematical Sciences
  4. Direct For Mathematical & Physical Scien [1510446] Funding Source: National Science Foundation

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This paper discusses the simultaneous inference of mean parameters in a family of distributions with quadratic variance function. We first introduce a class of semiparametric/parametric shrinkage estimators and establish their asymptotic optimality properties. Two specific cases, the location-scale family and the natural exponential family with quadratic variance function, are then studied in detail. We conduct a comprehensive simulation study to compare the performance of the proposed methods with existing shrinkage estimators. We also apply the method to real data and obtain encouraging results.

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