Markov chain conditions for admissibility in estimation problems with quadratic loss
Consider 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.
|Admissibility (msc 62C15), General considerations (msc 62C05), Bayesian problems; characterization of Bayes procedures (msc 62C10), None of the above, but in MSC2010 section 62Cxx (msc 62C99)|
|CWI. Probability, Networks and Algorithms [PNA]|
Eaton, M.L. (1999). Markov chain conditions for admissibility in estimation problems with quadratic loss. CWI. Probability, Networks and Algorithms [PNA]. CWI.