A Gaussian sequence approach for proving minimaxity: A Review
نویسندگان
چکیده
This paper reviews minimax best equivariant estimation in these invariant problems: a location parameter, scale parameter and (Wishart) covariance matrix. We briefly review development of the estimator as generalized Bayes relative to right Haar measure each case. Then we prove minimaxity procedure by giving least favorable prior sequence based on non-truncated Gaussian distributions. The results this are all known, but bring fresh somewhat unified approach using, contrast most proofs literature, smooth non truncated priors. leads some simplifications proofs.
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ژورنال
عنوان ژورنال: Journal of Statistical Planning and Inference
سال: 2021
ISSN: ['1873-1171', '0378-3758']
DOI: https://doi.org/10.1016/j.jspi.2020.06.007