Conditional Specification of Statistical Models [Hardcover]

Efforts to visualize multivariate densities necessarily involve the use of cross-sections, or, equivalently, conditional densities. This book focuses on distributions that are completely specified in terms of conditional densities. They are appropriately used in any modeling situation where conditional information is completely or partially available. All statistical researchers seeking more flexible models than those provided by classical models will find conditionally specified distributions of interest.Conditional Specification: Concepts and Theorems.- Exact and Near Compatibility in Distributions with Finite Support Sets.- Distributions with Normal Conditionals.- Conditionals in Exponential Families.- Other Conditionally Specified Families.- Improper and Nonstandard Models.- Characterizations Involving Conditional Moments.- Multivariate Extensions.- Estimation in Conditionally Specified Models.- Marginal and Conditional Specification in General.- Conditional Survival Models.- Applications to Modeling Bivariate Extremes.- Bayesian Analysis Using Conditionally Specified Models.- Conditional Specification Versus Simultaneous Equation Models.- Paella.

From the reviews:

JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION

&clearly written and accessible with relatively few mathematical prerequisites. I found surprisingly few typographical errors; the authors are to be congratulated for this&Each chapter contains numerous exercises. These exercises appear to be at an appropriate level for a graduate course in statistics, and appear to provide appropriate reinforcement for the material in the preceding chapters.

B.J.T. Morgan in Short Book Reviews , Vol. 20/3, December 2000

The book is well written, and presents clearly an important and developing subject.

This research monograph will be of interest to mathematical statisticians.