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.

1. Preliminaries 2. Some general concepts 3. First-order theory 4. Higher-order theory: Preliminaries and motivations 5. Some tools of higher-order theory 6. Higher-order theory: Likelihood combinants 7. Higher-order theory: Some further results and tools 8. Various notions of pseudo-likelihood and higher-order theory 9. Further aspect

"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