Synopses & Reviews
The concept of conditional specification of distributions is not new but, except in normal families, it has not been well developed in the literature. Computational difficulties undoubtedly hindered or discouraged developments in this direction. However, such roadblocks are of dimished importance today. Questions of compatibility of conditional and marginal specifications of distributions are of fundamental importance in modeling scenarios. Models with conditionals in exponential families are particularly tractable and provide useful models in a broad variety of settings.
Review
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."
Review
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."
Synopsis
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.
Table of Contents
Conditional Specification.- Basic Theorems.- Exact and Almost-Exact Compatibility in Discrete Distributions.- Distributions with Normal Conditionals.- Conditionals in Exponential Families.- Other Conditionally Specified Families.- Impossible Models.- Characterizations Involving Conditional Moments.- Multivariate Extensions.- Parameter Estimation in Conditionally Specified Models.- Simulations.- Marginal and Conditional Specification of Distributions.- Conditional Survival Models.- Bivariate Extreme Models Based on CS.- Bayesian Analysis Using Conditionally Specified Models.- Conditional Specification of Simultaneous Equation Models.- Other Conditional Specification Cases.