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Springer Texts in Statistics

A Course in Mathematical Statistics and Large Sample Theory

Authors: Bhattacharya, Rabi, Lin, Lizhen, Patrangenaru, Victor

  • Large Sample Theory with many worked examples, numerical calculations, and simulations to illustrate theory
  • Appendices provide ready access to a number of standard results, with many proofs
  • Solutions given to a number of selected exercises from Part I
  • Part II exercises with a certain level of difficulty appear with detailed hints
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Buy this book

eBook $79.99
price for Mexico (gross)
  • ISBN 978-1-4939-4032-5
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $99.99
price for Mexico
  • ISBN 978-1-4939-4030-1
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $99.99
price for Mexico
  • ISBN 978-1-4939-8159-5
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
About this Textbook

This graduate-level textbook is primarily aimed at graduate students of statistics, mathematics, science, and engineering who have had an undergraduate course in statistics, an upper division course in analysis, and some acquaintance with measure theoretic probability. It provides a rigorous presentation of the core of mathematical statistics.
Part I of this book constitutes a one-semester course on basic parametric mathematical statistics. Part II deals with the large sample theory of statistics - parametric and nonparametric, and its contents may be covered in one semester as well. Part III provides brief accounts of a number of topics of current interest for practitioners and other disciplines whose work involves statistical methods.

About the authors

Rabi Bhattacharya, PhD, has held regular faculty positions at UC, Berkeley; Indiana University; and the University of Arizona.  He is a Fellow of the Institute of Mathematical Statistics and a recipient of the U.S. Senior Scientist Humboldt Award and of a Guggenheim Fellowship.  He has served on editorial boards of many international journals and has published several research monographs and graduate texts on probability and statistics, including Nonparametric Inference on Manifolds, co-authored with A. Bhattacharya.

Lizhen Lin, PhD, is Assistant Professor in the Department of Statistics and Data Science at the University of Texas at Austin.  She received a PhD in Mathematics from the University of Arizona and was a Postdoctoral Associate at Duke University.  Bayesian nonparametrics, shape constrained inference, and nonparametric inference on manifolds are among her areas of expertise. 

Vic Patrangenaru, PhD, is Professor of Statistics at Florida State University.  He received PhDs in Mathematics from Haifa, Israel, and from Indiana University in the fields of differential geometry and statistics, respectively.  He has many research publications on Riemannian geometry and especially on statistics on manifolds.  He is a co-author with L. Ellingson of Nonparametric Statistics on Manifolds and Their Applications to Object Data Analysis. 

Reviews

“It deals with advanced statistical theory with a special focus on statistical inference and large sample theory, aiming to cover the material for a modern two-semester graduate course in mathematical statistics. … Overall, the book is very advanced and is recommended to graduate students with sound statistical backgrounds, as well as to teachers, researchers, and practitioners who wish to acquire more knowledge on mathematical statistics and large sample theory.” (Lefteris Angelis, Computing Reviews, March, 2017)

“This is a very nice book suitable for a theoretical statistics course after having worked through something at the level of Casella & Berger, as well as some measure theory. … In addition to the exercises, which range from doable to interesting, there are several projects scattered throughout the text. The explanations are clear and crisp, and the presentation is interesting. … the book would be a worthy addition to your statistics library.” (Peter Rabinovitch, MAA Reviews, maa.org, March, 2017)



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Table of contents (15 chapters)

  • Introduction

    Bhattacharya, Rabi (et al.)

    Pages 3-9

  • Decision Theory

    Bhattacharya, Rabi (et al.)

    Pages 11-17

  • Introduction to General Methods of Estimation

    Bhattacharya, Rabi (et al.)

    Pages 19-37

  • Sufficient Statistics, Exponential Families, and Estimation

    Bhattacharya, Rabi (et al.)

    Pages 39-65

  • Testing Hypotheses

    Bhattacharya, Rabi (et al.)

    Pages 67-113

Buy this book

eBook $79.99
price for Mexico (gross)
  • ISBN 978-1-4939-4032-5
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $99.99
price for Mexico
  • ISBN 978-1-4939-4030-1
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $99.99
price for Mexico
  • ISBN 978-1-4939-8159-5
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
A Course in Mathematical Statistics and Large Sample Theory
Authors
Series Title
Springer Texts in Statistics
Copyright
2016
Publisher
Springer-Verlag New York
Copyright Holder
Springer Science+Business Media, LLC, part of Springer Nature
eBook ISBN
978-1-4939-4032-5
DOI
10.1007/978-1-4939-4032-5
Hardcover ISBN
978-1-4939-4030-1
Softcover ISBN
978-1-4939-8159-5
Series ISSN
1431-875X
Edition Number
1
Number of Pages
XI, 389
Number of Illustrations
7 b/w illustrations, 2 illustrations in colour
Topics