Advances on Models, Characterizations and Applications

Statistical distributions 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. This work offers information on the many developments in the field.

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.