A Course in Mathematical Statistics and Large Sample Theory : Springer Texts in Statistics - Lizhen Lin

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A Course in Mathematical Statistics and Large Sample Theory

By: Lizhen Lin, Victor Patrangenaru, Rabi Bhattacharya

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Hardcover | 8 September 2016

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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.

Industry 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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