| Author : | Tian, Guo-Liang; Tan, Ming; Ng, Kai-Wang; Tang, Man-Lai |
|---|---|
| Category : | Journal Article |
| Department : | |
| Year / Month : | 2009 |
| ISSN: | 0361-0926 |
| Source : | Communications in Statistics – Theory and Methods, 38, 115 - 129. |
Abstract
- Checking compatibility for two given conditional distributions and identifying the corresponding unique compatible marginal distributions are important problems in mathematical statistics, especially in Bayesian inferences. In this article, we develop a unified method to check the compatibility and uniqueness for two finite discrete conditional distributions. By formulating the compatibility problem into a system of linear equations subject to constraints, it can be reduced to a quadratic optimization problem with box constraints. We also extend the proposed method from two-dimensional cases to higher-dimensional cases. Finally, we show that our method can be easily applied to checking compatibility and uniqueness for a regression function and a conditional distribution. Several numerical examples are used to illustrate the proposed method. Some comparisons with existing methods are also presented.
Keywords
Related Publication
- Optimal Baggage Limit Policy: Airline Passenger and Cargo Allocation
- Efficient semiparametric estimation via Cholesky decomposition for longitudinal data
- Constrained maximum likelihood estimation for two-level mean and covariance structure models
- An unified method for checking compatibility and uniqueness for finite discrete conditional distributions
- Efficient methods for estimating constrained parameters with applications to lasso logistic regression