372 Pages
by
Chapman & Hall
360 Pages
by
Routledge
Also available as eBook on:
This book provides a systematic account of some developments in asymptotic parametric inference from a likelihood-based perspective. It focuses on first-order asymptotic theory, and discusses the need for higher-order theory.
Introduction
Preliminaries
Some general concepts
First order theory
Higher order theory:preliminaries
Mathematical basis of higher order theory
Higher order theory: likelihood combinants
higher order theory: some further results and tools
Various notions of likelihood and higher order theory
Further aspects
References
Index
Preliminaries
Some general concepts
First order theory
Higher order theory:preliminaries
Mathematical basis of higher order theory
Higher order theory: likelihood combinants
higher order theory: some further results and tools
Various notions of likelihood and higher order theory
Further aspects
References
Index
Biography
D.R. Cox
"The book succeeds in bringing together a large amount of useful and interesting work."
-Short Book Reviews
"The book is carefully structured. The presentation is generally graded so that motivations, concepts, and results are first discussed, at least briefly, with a minimum of technicalities, and then more complete details are given...usually illustrated with several examples. This style is very helpful and allows the casual reader to grasp the purposes and flow of the developments without requiring that every derivation be followed."
-Journal of the American Statistical Association
"This is an authoritative and comprehensive book which develops its complex theoretical results in a coherent and logical manner. Anybody interested in recent developments in parametric likelihood theory should read it."
-The Statistician