
Mathematical Statistics
Jun Shao(Author)
Springer (Publisher)
Published on 29. May 1999
Book
Hardback
XIV, 530 pages
978-0-387-98674-6 (ISBN)
Article exhausted; check for reprint
Description
This graduate textbook covers those topics in statistical theory essential for students preparing for work on a Ph.D. degree in statistics. The first chapter provides a quick overview of concepts and results in measure-theoretic probability theory that are useful in statistics, while the second introduces some fundamental concepts in statistical decision theory and inference. The remaining chapters contain detailed studies on such important topics as: unbiased estimation, parametric estimation, nonparametric estimation, hypothesis testing, and confidence sets. A large number of exercises in each chapter provide not only practice problems for students, but also many additional results. In addition to the classical results that are typically covered in a textbook of this level, this book introduces some topics in modern statistical theory that have been developed in recent years, such as Markov chain Monte Carlo, quasi-likelihoods, empirical likelihoods, statistical functionals, generalized estimation equations, the jackknife, and the bootstrap.
More details
Series
Language
English
Place of publication
NY
United States
Target group
College/higher education
Professional and scholarly
Illustrations
Illustrations
Dimensions
Height: 230 mm
Weight
900 gr
ISBN-13
978-0-387-98674-6 (9780387986746)
DOI
10.1007/b98900
Schweitzer Classification
Other editions
New editions

Additional editions

Content
Probability Theory * Fundamentals of Statistics * Unbiased Estimation * Estimation in Parametric Models * Estimation in Nonparametric Models * Hypothesis Tests * Confidence Sets