MATHEMATICAL STATISTICS JUN SHAO PDF
Jun Shao. Mathematical Statistics. Second Edition measure and f is called its probability density function (p.d.f.) w.r.t. ν. For any probability measure P on (Rk. This graduate textbook covers topics in statistical theory essential for graduate DRM-free; Included format: PDF; ebooks can be used on all reading devices. Jun Shao. Mathematical Statistics. Springer Mathematical statistics / Jun Shao. p. cm. measure and f is called its probability density function (p.d.f.) w.r.t. ν.
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Jun Shao. Department of Statistics. University of Wisconsin. Madison, WI USA [email protected] Library of Congress Control Number: Jun Shao is Professor of Statistics at the University of Wisconsin, Madison. Springer Science & Business Media, Jul 17, - Mathematics - pages. This book is intended for a course entitled Mathematical Statistics o?ered at the DRM-free; Included format: PDF; ebooks can be used on all reading devices.
Mathematical Statistics: Exercises and Solutions
Each chapter contains a number of examples. Some of them are designed as materials covered in the discussion section of this course, which is typically taught by a teaching assistant a senior graduate student.
The exercises in each chapter form an important part of the book. They provide not only practice problems for students, but also many additional results as complementary materials to the main text.
The book is essentially based on 1 my class notes taken in when I was a student in this course, 2 the notes I used when I was a teaching assistant for this course in , and 3 the lecture notes I prepared during as the instructor of this course.
I would like to express my thanks to Dennis Cox, who taught this course when I was a student and a teaching assistant, and undoubtedly has influenced my teaching style and textbook for this course.
I am also very grateful to students in my class who provided helpful comments; to Mr. Yonghee Lee, who helped me to prepare all the figures in this book; to the Springer-Verlag production and copy editors, who helped to improve the presentation; and to my family members, who provided support during the writing of this book. Madison, Wisconsin January Jun Shao Preface to the Second Edition In addition to correcting typos and errors and making a better presentation, the main effort in preparing this new edition is adding some new material to Chapter 1 Probability Theory and a number of new exercises to each chapter.
The structure of the book remains the same. As a result, Chapter 1 of the new edition is self-contained for important concepts, results, and proofs in probability theory with emphasis in statistical applications. Since the original book was published in , I have been using it as a textbook for a two-semester course in mathematical statistics.
Exercise problems accumulated during my teaching are added to this new edition. Some exercises that are too trivial have been removed. In the original book, indices on definitions, examples, theorems, propositions, corollaries, and lemmas are included in the subject index.
In the new edition, they are in a separate index given in the end of the book prior to the author index. In addition to improving the presentation, the new edition makes Chapter 1 a self-contained chapter for probability theory with emphasis in statistics.
Added topics include useful moment inequalities, more discussions of moment generating and characteristic functions, conditional independence, Markov chains, martingales, Edgeworth and Cornish-Fisher expansions, and proofs to many key theorems such as the dominated convergence theorem, monotone convergence theorem, uniqueness theorem, continuity theorem, law of large numbers, and central limit theorem.
A new section in Chapter 5 introduces semiparametric models, and a number of new exercises were added to each chapter.
The revised and updated version remains of high quality, and I recommend it for use as a text or reference book in a graduate statistics program. The main changes include addition of new material in Chapter 1, addition and deletion of a number of exercises, addition of two new sub-sections ….
The book remains valuable to instructors and graduate students of traditional mathematical statistics courses, specially for its large collection of problems and for its rigourous presentation.
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download eBook. Jun Shao. This graduate textbook covers topics in statistical theory essential for graduate students preparing for work on a Ph. The first chapter provides a quick overview of concepts and results in measure-theoretic probability theory that are usefulin statistics.
The second chapter introduces some fundamental concepts in statistical decision theory and inference. Chapters contain detailed studies on some important topics: A large number of exercises in each chapter provide not only practice problems for students, but also many additional results.No trivia or quizzes yet.
The revised and updated version remains of high quality, and I recommend it for use as a text or reference book in a graduate statistics program. Refresh and try again.
A new section in Chapter 5 introduces semiparametric models, and a number of new exercises were added to each chapter. download eBook.
In addition to improving the presentation, the new edition makes Chapter 1 a self-contained chapter for probability theory with emphasis in statistics. The first chapter provides a quick overview of concepts and results in measure-theoretic probability theory that are usefulin statistics. The Indian Journal of Statistics, Vol. Shaun Zhang rated it really liked it Feb 19,
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