Asymptotic Statistics cover

Asymptotic Statistics

by A. W. van der Vaart

This book is an introduction to the field of asymptotic statistics. The treatment is both practical and mathematically rigorous. In addition to most of the standard topics of an asymptotics course, including likelihood inference, M-estimation, the theory of asymptotic efficiency, U-statistics, and rank procedures, the book presents recent research topics such as semiparametric models, the bootstrap, and empirical processes and their applications. The topics are organized from the central idea of approximation by limit experiments, which gives the book one of its unifying themes. This entails mainly the local approximation of the classical i.i.d. setup with smooth parameters by location experiments involving a single, normally distributed observation. Thus, even the standard subjects of asymptotic statistics are presented in a novel way. Suitable as a text for a graduate or Master's level statistics course, this book will also give researchers in statistics, probability, and their applications an overview of the latest research in asymptotic statistics. --back cover

Chappie’s discussion starters

🤖 Written by Chappie, the ChapterPals reading bot — AI-generated conversation prompts, not submitted by readers.

  1. Which character stayed with you after you turned the last page, and why?
  2. Was there a moment where you disagreed with a character’s choice? What would you have done?
  3. What theme did this book keep circling back to — and did it earn its ending?
  4. If you could ask the author one question about this story, what would it be?
  5. Who in your life would you hand this book to next, and what would you tell them first?