Add to ORKGConsider the problem of estimating a parametric function when the loss is quadratic. Given an improper prior distribution, there is a formal Bayes estimator for the parametric function. Associated with the estimation problem and the improper prior is a symmetric Markov chain. It is shown that if the Markov chain is recurrent, then the formal Bayes estimator is admissible. This result is used to provide a new proof of the admissibility of Pitman's estimator of a location parameter in one and two dimensions
Conditions are given for admissibility of procedures invariant under two-dimensional translation. Th...
Consider nonparametric problems of estimating an unknown distribution function, F, under the loss L(...
In some invariant estimation problems under a group, the Bayes estimator against an invariant prior ...
We consider evaluation of proper posterior distributions obtained from improper prior distributions....
Abstract. We consider evaluating improper priors in a formal Bayes setting according to the conseque...
This paper is devoted to the linear admissible estimate and admissible estimate in the class of homo...
For estimation problems, an interesting question is whether the maximum likelihood estimator(MLE) is...
Consider a parametric statistical model, P (dx|θ), and an improper prior distribution, ν(dθ), that t...
Consider a parametric statistical model P(dx|θ)and an improper prior distribution ν(dθ)that together...
The stepwise Bayes technique is a simple but versatile method for proving admissibility of estimator...
In the first part of this paper, we give a complete characterization of the class, A<SUB>W</SUB>(K&...
Graduation date: 1986We describe a general finite-dimensional inner product space setting for studyi...
For estimation problems, an interesting question is whether the maximum likelihood estimator(MLE) is...
Consider truncated Poisson distributions and their reasonable estimators. Even though the estimators...
The focus of this paper is on using observations to estimate an unknown probability vector p = (p1,....
Conditions are given for admissibility of procedures invariant under two-dimensional translation. Th...
Consider nonparametric problems of estimating an unknown distribution function, F, under the loss L(...
In some invariant estimation problems under a group, the Bayes estimator against an invariant prior ...
We consider evaluation of proper posterior distributions obtained from improper prior distributions....
Abstract. We consider evaluating improper priors in a formal Bayes setting according to the conseque...
This paper is devoted to the linear admissible estimate and admissible estimate in the class of homo...
For estimation problems, an interesting question is whether the maximum likelihood estimator(MLE) is...
Consider a parametric statistical model, P (dx|θ), and an improper prior distribution, ν(dθ), that t...
Consider a parametric statistical model P(dx|θ)and an improper prior distribution ν(dθ)that together...
The stepwise Bayes technique is a simple but versatile method for proving admissibility of estimator...
In the first part of this paper, we give a complete characterization of the class, A<SUB>W</SUB>(K&...
Graduation date: 1986We describe a general finite-dimensional inner product space setting for studyi...
For estimation problems, an interesting question is whether the maximum likelihood estimator(MLE) is...
Consider truncated Poisson distributions and their reasonable estimators. Even though the estimators...
The focus of this paper is on using observations to estimate an unknown probability vector p = (p1,....
Conditions are given for admissibility of procedures invariant under two-dimensional translation. Th...
Consider nonparametric problems of estimating an unknown distribution function, F, under the loss L(...
In some invariant estimation problems under a group, the Bayes estimator against an invariant prior ...