Results 221 to 230 of about 9,519 (266)

Variance of Bayes estimates

IEEE Transactions on Information Theory, 1971
This paper contains an analysis of the performance of Bayes conditional-mean parameter estimators. The main result is that on a finite parameter space such estimates exhibit a mean-square error that diminishes exponentially with the number of observations, the observations being assumed to be independent.
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Bayes empirical Bayes estimation of a poisson mean

Statistics & Probability Letters, 1985
In the empirical Bayes (EB) decision problem consisting of squared error estimation of a Poisson mean, a prior distribution \(\Lambda\) is placed on the gamma family of prior distributions to produce Bayes EB estimators which are admissible. A subclass of such estimators is shown to be asymptotically optimal (a.o.).
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Some Comments on “Bayes” Estimators

The American Statistician, 1973
(1973). Some Comments on “Bayes” Estimators. The American Statistician: Vol. 27, No. 1, pp. 12-14.
G. C. Tiao, G. E. P. Box
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Sensitivity of bayes and empirical bayes estimates

Communications in Statistics - Theory and Methods, 1990
The main objective is to investigate the behaviour of Bayes and empirical Bayes confidence intervals for a mean to changes from normality in the specification of either the sampling or prior distributions. To do this the posterior mean and variance are calculated when the prior and sampling distributions are defined by Edgeworth expansions, corrective ...
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Bayes Estimates of Haplotype Effects

Genetic Epidemiology, 2001
We describe a Markov chain Monte Carlo implementation of a Bayesian approach to estimating associations of a trait with a large set of haplotypes recently introduced by Clayton and Jones [Am J Hum Genet 65:1161–9, 2000]. The model uses the length of the longest segment in common between any two haplotypes to define the prior correlation structure for ...
D C, Thomas, J L, Morrison, D G, Clayton
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ESTIMATING A BINOMIAL PARAMETER: IS ROBUST BAYES REAL BAYES?

Statistics & Risk Modeling, 1993
Summary: In robust Bayesian analysis, a prior is assumed to belong to a family instead of being specified exactly. The multiplicity of priors naturally leads to a collection of Bayes actions (estimates), and these often form a convex set (an interval in the case of a real parameter).
Zen, Mei-Mei, DasGupta, A.
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ON THE CONSISTENCY OF HIERARCHICAL BAYES ESTIMATORS

Statistics & Risk Modeling, 1996
Summary: In considering Bayesian estimation of multivariate normal mean, \textit{G. S. Datta} and \textit{M. Ghosh} [J. Stat. Plann. Inference 29, No. 3, 229-243 (1991; Zbl 0756.62014)] proposed hierarchical Bayes estimators and studied their asymptotic optimality property. A conjecture was raised therein.
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Bayes estimation of a convex quadratic

Biometrika, 1973
SUMMARY The estimation of a quadratic regression curve when the quadratic coefficient is known to be positive is treated by a Bayesian method. The method extends easily to deal with a general linear model under parameter constraints.
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Limiting the Risk of Bayes and Empirical Bayes Estimators--Part I: The Bayes Case

Journal of the American Statistical Association, 1971
Abstract The first part of this article considers the Bayesian problem of estimating the mean, θ, of a normal distribution when the mean itself has a normal prior. The usual Bayes estimator for this situation has high risk if θ is far from the mean of the prior distribution.
Bradley Efron, Carl Morris
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