Title
Random Probability Measures with Given Mean and Variance Running title: Random Probability Measures
Recommended Citation
Postprint version. Published in Journal of Theoretical Probability, Volume 15, Issue 4, January 1, 2002, pages 919-938.
Copyright © 2002 Springer.
NOTE: At the time of publication, the author Theodore P. Hill was not yet affiliated with Cal Poly.
The definitive version is available at https://doi.org/10.1023/A:1020688620366.
Abstract
This article describes several natural methods of constructing random probability measures with prescribed mean and variance, and focuses mainly on a technique which constructs a sequence of simple (purely discrete, finite number of atoms) distributions with the prescribed mean and with variances which increase to the desired variance. Basic properties of the construction are established, including conditions guaranteeing full support of the generated measures, and conditions guaranteeing that the final measure is discrete. Finally, applications of the construction method to optimization problems such as Plackett’s Problem are mentioned, and to experimental determination of average-optimal solutions of certain control problems.
Disciplines
Mathematics
URL: https://digitalcommons.calpoly.edu/rgp_rsr/11