Bayes Estimators for the Continuous Uniform Distribution


Authors: 
Rossman, A. J., Short, T. H., & Parks, M. T.
Category: 
Volume: 
6(3)
Pages: 
Online
Year: 
1998
Publisher: 
Journal of Statistics Education
URL: 
http://www.amstat.org/publications/jse/v6n3/rossman.html
Abstract: 

Classical estimators for the parameter of a uniform distribution on the interval are often discussed in mathematical statistics courses, but students are frequently left wondering how to distinguish which among the variety of classical estimators are better than the others. We show how classical estimators can be derived as Bayes estimators from a family of improper prior distributions. We believe that linking the estimation criteria in a Bayesian framework is of value to students in a mathematical statistics course, and we believe that the students benefit from the exposure to Bayesian methods. In addition, we compare classical and Bayesian interval estimators for the parameter Phi and illustrate the Bayesian analysis with an example.

The CAUSE Research Group is supported in part by a member initiative grant from the American Statistical Association’s Section on Statistics and Data Science Education