Density Prediction and the Stein Phenomenon
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DOI: 10.1007/s13171-019-00186-z
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- Kengo Kato, 2009. "Improved prediction for a multivariate normal distribution with unknown mean and variance," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 61(3), pages 531-542, September.
- Komaki, Fumiyasu, 2015. "Simultaneous prediction for independent Poisson processes with different durations," Journal of Multivariate Analysis, Elsevier, vol. 141(C), pages 35-48.
- Tsukuma, Hisayuki & Kubokawa, Tatsuya, 2017. "Proper Bayes and minimax predictive densities related to estimation of a normal mean matrix," Journal of Multivariate Analysis, Elsevier, vol. 159(C), pages 138-150.
- Takeru Matsuda & Fumiyasu Komaki, 2015. "Singular value shrinkage priors for Bayesian prediction," Biometrika, Biometrika Trust, vol. 102(4), pages 843-854.
- Ghosh, Malay & Mergel, Victor & Datta, Gauri Sankar, 2008. "Estimation, prediction and the Stein phenomenon under divergence loss," Journal of Multivariate Analysis, Elsevier, vol. 99(9), pages 1941-1961, October.
- José Manuel Corcuera & Federica Giummolè, 1999. "A Generalized Bayes Rule for Prediction," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 26(2), pages 265-279, June.
- A. Boisbunon & Y. Maruyama, 2014. "Inadmissibility of the best equivariant predictive density in the unknown variance case," Biometrika, Biometrika Trust, vol. 101(3), pages 733-740.
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Keywords
Divergence loss; Dominance property; Empirical Bayes; Hellinger-Bhattacharyya divergence; Kullback-Leibler divergence; Minimaxity; Normal distribution; Poisson distribution; Risk function; Shrinkage estimator; Simultaneous estimation; Superharmonic;All these keywords.
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