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Advances on Models, Characterizations and Applications is timely reference that offers up-to-date information on many recent advances in the field. Comprising fourteen self-contained chapters contributed by internationally renowned experts, it delineates recent developments on the characterizations and other important properties of several distributions, inferential issues related to these models, and several applications of the models to real-world problems. Each chapter is rich with references for further study or more in-depth information on each topic. As a whole, the book reflects the deep importance of the properties of statistical distributions and is a wecome addition to the literature.
List of contents
The Shapes of the Probability Density, Hazard, and Reverse Hazard Functions. Stochastic Ordering of Risks, Influence of Dependence, and A.S. Constructions. The q-Factorial Moments of Discrete q-Distributions and a Characterization of the Euler Distribution. On the Characterization of Distributions Through the Properties of Conditional Expectations of Order Statistics. Characterization of the Exponential Distribution by Conditional Expectations of Generalized Spacings. Some Characterizations of Exponential Distribution Based on Progressively Censored Order Statistics. A Note on Regressing Order Statistics and Record Values. Generalized Pareto Distributions and Their Characterizations. On Characteristic Properties of the Uniform Distribution. Characterizations of Multivariate Distributions Involving Conditional Specification and/or Hidden Truncation. Bivariate Matsumoto-Yor Property and Related Characterizations. First Principal Component Characterization of a Continuous Random Variable. The Lawless-Wang's Operational Ridge Regression Estimator Under the Linex Loss Function. On the Distributions of the Reference Dose and Its Application in Health Risk Assessment. Subject Index.
About the author
N. Balakrishnan, I. G. Bairamov, O. L. Gebizlioglu
Summary
Statistical distributions are one of the most important applied mathematical tools across a wide spectrum of disciplines, including engineering, biological sciences, and health and social sciences. Since they are used to model observed data and ultimately to develop inferential procedures, understanding the properties of statistical distributions is critical to developing optimal inferential methods and validating the resulting model assumptions. Advances on Models, Characterizations and Applications offers up-to-date information on many recent developments in the field.
Comprising fourteen self-contained chapters contributed by internationally renowned experts, this book delineates recent developments on characterizations and other important properties of several distributions, inferential issues related to these models, and several applications of the models to real-world problems. Each chapter is rich with references for further study or more in-depth information on each topic and reflects work presented at the International Conference on Advances on Characterizations, Models, and Applications held in Antalya, Turkey in December 2001.
Advances on Models, Characterizations and Applications provides an updated account of important properties of statistical distributions that reflects their deep importance and broad application and is a welcome addition to the literature.
