4.6 Article

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

期刊

ANNALS OF STATISTICS
卷 44, 期 2, 页码 564-597

出版社

INST MATHEMATICAL STATISTICS
DOI: 10.1214/15-AOS1377

关键词

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

资金

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

向作者/读者索取更多资源

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.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据