Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Gaussian sequence approach for proving minimaxity: A Review   This paper reviews minimax best equivariant estimation in these invariant
estimation problems: a location parameter, a scale parameter and a (Wishart)
covariance matrix. We briefly review development of the best equivariant
estimator as a generalized Bayes estimator relative to right invariant Haar
measure in each case. Then we prove minimaxity of the best equivariant
procedure by giving a least favorable prior sequence based on non-truncated
Gaussian distributions. The results in this paper are all known, but we bring a
fresh and somewhat unified approach by using, in contrast to most proofs in the
literature, a smooth sequence of non truncated priors. This approach leads to
some simplifications in the minimaxity proofs.

18
The categories of this paper are: econ
27
The categories of this paper are: comp-gas
14
The categories of this paper are: math-ph
19
The categories of this paper are: eess
28
The categories of this paper are: alg-geom
8
The categories of this paper are: hep-ex
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The categories of this paper are: nlin
11
The categories of this paper are: hep-lat
25
The categories of this paper are: patt-sol
3
The categories of this paper are: physics
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The categories of this paper are: dg-ga
7
The categories of this paper are: hep-th
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The categories of this paper are: nucl-th
6
The categories of this paper are: astro-ph
31
The categories of this paper are: ao-sci
13
The categories of this paper are: quant-ph