Minimax estimators of a normal variance

Metrika

Volumn 48, Issue 3, 1998, Pages 209-214

  Maruyama, Yuzo ^a  

^a KYUSHU UNIVERSITY   (Japan)

Author keywords

Minimax; Stein's estimator; Variance estimation

Indexed keywords

EID: 0033472540     PISSN: 00261335     EISSN: None     Source Type: Journal    
DOI: 10.1007/PL00003974     Document Type: Article

References (9)

1. Abramowitz M, Stegun IA (1964) Handbook of mathematical functions. Dover Publications, New York
2. Brewster JF, Zidek JV (1974) Improving on equivariant estimators. Ann Statist 2:21-38
3. Ghosh M (1994) On some Bayesian solutions of the Neyman-Scott problem. In: Statistical Decision Theory and Related Topics V, Springer-Verlag, New York, pp. 267-276
4. Kubokawa T (1994) An unified approach to improving equivariant estimators. Ann Statist 22:290-299
5. Maruyama Y (1998) Improving on the James-Stein estimator.to appear in Statistics & Decisions
6. Proskin HM (1985) An admissibility theorem with applications to the estimation of variance of the normal distribution. Ph.D dissertation, Dept Statist, Rutgers University
7. Rukhin AL (1987) How much better are better estimators of a normal variance? 82:925-928
8. Rukhin AL (1992) Asymptotic risk behavior of mean vector and variance estimators and the problem of positive mean. Ann Inst Statist Math 44:299-311
9. Stein C (1964) Inadmissibility of the usual estimator for the variance of a normal distribution with unknown mean. Ann Inst Statist Math 16:155-160