The only single-source----now completely updated and revised----to offer a unified treatment of the theory, methodology, and applications of the EM algorithm

Complete with updates that capture developments from the past decade, The EM Algorithm and Extensions, Second Edition successfully provides a basic understanding of the EM algorithm by describing its inception, implementation, and applicability in numerous statistical contexts. In conjunction with the fundamentals of the topic, the authors discuss convergence issues and computation of standard errors, and, in addition, unveil many...

Presenting information on logistic regression models, this work explains difficult concepts through illustrative examples.

An up-to-date approach to understanding statistical inference

Statistical inference is finding useful applications in numerous fields, from sociology and econometrics to biostatistics. This volume enables professionals in these and related fields to master the concepts of statistical inference under inequality constraints and to apply the theory to problems in a variety of areas.

Constrained Statistical Inference: Order, Inequality, and Shape Constraints provides a unified and up-to-date treatment of the methodology. It clearly illustrates concepts with practical examples from a variety...

Covering the first full year of experimental design topics at the beginning graduate level, this text presents complete coverage of the subject matter, with equal emphasis on design and analysis.

A valuable guide to conducting experiments and analyzing data across a wide range of applications
Experimental design is an important component of the scientific method. This book provides guidance on planning efficient investigations. It compiles designs for a wide range of experimental situations not previously found in accessible form. Focusing on applications in the physical, engineering, biological, and social sciences, Planning, Construction, and Statistical Analysis of Comparative Experiments is a valuable guide to designing experiments and correctly analyzing and interpreting the...

"C. R. Rao would be found in almost any statistician's list of five outstanding workers in the world of Mathematical Statistics today. His book represents a comprehensive account of the main body of results that comprise modern statistical theory."
-W. G. Cochran

" C. R. Rao is] one of the pioneers who laid the foundations of statistics which grew from ad hoc origins into a firmly grounded mathematical science."
-B. Efrom

Translated into six major languages of the world, C. R. Rao's Linear Statistical Inference and Its Applications is one of the foremost...

Approximation Theorems of Mathematical Statistics

This convenient paperback edition makes a seminal text in statistics accessible to a new generation of students and practitioners. Approximation Theorems of Mathematical Statistics covers a broad range of limit theorems useful in mathematical statistics, along with methods of proof and techniques of application. The manipulation of "probability" theorems to obtain "statistical" theorems is emphasized. Besides a knowledge of these basic statistical theorems, this lucid introduction to the subject imparts an appreciation of the...

This title offers an accessible introduction to the use of regression analysis in the social sciences. It has the most complete and fully integrated coverage of regression modeling currently available for graduate-level behavioral science students and practitioners. Covering techniques that span the full spectrum of levels of measurement for both continuous and limited response variables, and using examples taken from such disciplines as sociology, psychology, political science, and public health, the author succeeds in demystifying an academically rigorous subject and making it accessible to...

Stock market investors have very different reactions to downside versus upside risk. This book begins by explaining the current treatment of stock market risk and methods of lowering that risk. The authors then show that many types of asymmetry of stock returns or investor reactions cause the existing theory to fail. They present the theory of downside risk and utility theory to account for the asymmetry, showing how the previous model can be adjusted for downside risk.

At last--a social scientist's guide through the pitfalls of modern statistical computing

Addressing the current deficiency in the literature on statistical methods as they apply to the social and behavioral sciences, Numerical Issues in Statistical Computing for the Social Scientist seeks to provide readers with a unique practical guidebook to the numerical methods underlying computerized statistical calculations specific to these fields. The authors demonstrate that knowledge of these numerical methods and how they are used in statistical packages is essential for making accurate...