Random Probability Measures with Given Mean and Variance Running title: Random Probability MeasuresJournal of Theoretical Probability
AbstractThis 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.
Citation InformationLisa Bloomer and Theodore P. Hill. "Random Probability Measures with Given Mean and Variance Running title: Random Probability Measures" Journal of Theoretical Probability Vol. 15 Iss. 4 (2002) p. 919 - 938
Available at: http://works.bepress.com/tphill/32/