Shrinkage estimation of location parameters in a multivariate skew-normal distribution
DOI10.1080/03610926.2019.1568481OpenAlexW2912397512WikidataQ128424916 ScholiaQ128424916MaRDI QIDQ5077405
William E. Strawderman, Ryota Yuasa, Tatsuya Kubokawa
Publication date: 18 May 2022
Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/03610926.2019.1568481
decision theoryempirical Bayesminimaxitymultivariate skew-normal distributionrisk functionquadratic loss functiondominance resultmean mixture of normal distributions
Point estimation (62F10) Bayesian inference (62F15) Minimax procedures in statistical decision theory (62C20) Statistics (62-XX) Empirical decision procedures; empirical Bayes procedures (62C12) Admissibility in statistical decision theory (62C15)
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Cites Work
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- Statistical decision theory and Bayesian analysis. 2nd ed
- Estimation of the mean of a multivariate normal distribution
- A multivariate skew normal distribution.
- A class of multivariate skew-normal models
- Skewed multivariate models related to hidden truncation and/or selective reporting. With discussion and a rejoinder by the authors.
- Data Analysis Using Stein's Estimator and its Generalizations
- Statistical Applications of the Multivariate Skew Normal Distribution
- The multivariate skew-normal distribution
- Stein's Estimation Rule and Its Competitors--An Empirical Bayes Approach
- Proper Bayes Minimax Estimators of the Multivariate Normal Mean