Likelihood Methods in Statistics

This book is suitable for students and statisticians with a knowledge of graduate-level statistical theory. At least some background in classical likelihood theory is recommended, but the opening chapters provide a review for readers who lack such background. Severini (statistics, Northwestern University) intends his book as an introduction to the modern, alternative approach to likelihood inference. The text includes a discussion of asymptotic theory and conditional inference; the signed likelihood ratio statistic; likelihood functions for a parameter of interest; and the modified profile likelihood function. Each chapter includes extensive references to additional results, followed by exercises to illustrate concepts from the chapter. Solutions are not included in the text but are available from the author (e-mail address included in the Preface). Annotation c. Book News, Inc., Portland, OR (booknews.com)