Theoretical Statistics: Topics for a Core Course (Springer Texts in Statistics) 2010th Edition by Robert W. Keener (PDF)

Description

Intended as the text for a sequence of advanced courses, this book covers major topics in theoretical statistics in a concise and rigorous fashion. The discussion assumes a background in advanced calculus, linear algebra, probability, and some analysis and topology. Measure theory is used, but the notation and basic results needed are presented in an initial chapter on probability, so prior knowledge of these topics is not essential. The presentation is designed to expose students to as many of the central ideas and topics in the discipline as possible, balancing various approaches to inference as well as exact, numerical, and large sample methods. Moving beyond more standard material, the book includes chapters introducing bootstrap methods, nonparametric regression, equivariant estimation, empirical Bayes, and sequential design and analysis. The book has a rich collection of exercises. Several of them illustrate how the theory developed in the book may be used in various applications. Solutions to many of the exercises are included in an appendix.

User’s Reviews

Editorial Reviews: Review From the reviews:“The book is innovative in the presentation and in mashing the traditional material with modern topics. The presentation shows a great mastery of the subject. … recommended to someone who has a working knowledge of statistics and would like to learn more about the theory. … As a text for a course, the book is versatile. … The mathematical level is correct for a first year graduate course and may be appropriate at some universities for courses whose primary audience is seniors.” (Stephan Morgenthaler, Mathematical Reviews, Issue 2011 m)“This volume provides an excellent course in the mathematical theory underlying statistical ideas and methods, for advanced … students. The amount of material covered is indicated by the fact that it evolved from a three-semester sequence of courses given by the author. Its suitability as a course text is materially aided by very extensive exercises, along with solutions to selected exercises. Anyone who works through this book will end up with a first class understanding of the mathematical ideas underlying modern statistical concepts and methods.” (David J. Hand, International Statistical Review, Vol. 80 (1), 2012)“The book extensively covers classic and modern topics of theoretical statistics in a rigorous manner. … The book provides more than 400 exercise problems. … There are many books on statistical theory but very few have such great breadth and scope of materials as this book. … the book is well written and it is a great addition to the collection of books on statistical theory. … It will serve well both as a textbook and a reference book.” (Xianggui Qu, Technometrics, Vol. 53 (3), August, 2011) From the Back Cover Intended as the text for a sequence of advanced courses, this book covers major topics in theoretical statistics in a concise and rigorous fashion. The discussion assumes a background in advanced calculus, linear algebra, probability, and some analysis and topology. Measure theory is used, but the notation and basic results needed are presented in an initial chapter on probability, so prior knowledge of these topics is not essential. The presentation is designed to expose students to as many of the central ideas and topics in the discipline as possible, balancing various approaches to inference as well as exact, numerical, and large sample methods. Moving beyond more standard material, the book includes chapters introducing bootstrap methods, nonparametric regression, equivariant estimation, empirical Bayes, and sequential design and analysis. The book has a rich collection of exercises. Several of them illustrate how the theory developed in the book may be used in various applications. Solutions to many of the exercises are included in an appendix. Robert Keener is Professor of Statistics at the University of Michigan and a fellow of the Institute of Mathematical Statistics. About the Author Robert Keener is Professor of Statistics at the University of Michigan and a fellow of the Institute of Mathematical Statistics. Read more

Reviews from Amazon users which were colected at the time this book was published on the website:

⭐This book may well be one of only a very small handful of theoretical statistics book that is competently written.The problem with most statistics textbooks is that statistics is too difficult for statisticians. One obvious prerequisite for a proper understanding of statistics is a course covering real analysis, measure theory and probability theory. To the best of my knowledge, only UC Berkeley requires this of their Ph.D. students.In my considered view, nobody who isn’t fairly knowledgeable about probability theory, stochastic processes and stochastic differential equations, and functional analysis at the level of Walter Rudin’s classic textbook should presume to study statistics–let ALONE to write about it!This book is in a class by itself!Its natural companion (and prerequisite, to some extent) textbook on probability is the monumental “Foundations of Modern Probability,” by Olav Kallenberg.

⭐As to the book, this is a fantastic book in theory of statistics and one of the bests I have ever read in this field ( I have a Ph.D. in statistics from UC Berkeley). Without a doubt this book is well organized and super comprehensively goes over topics. Knowledge of probability theory and basic analysis are required.The reason I give this product only one star is because I ordered this book from amazon prime which mean paid about 20$ more compared to other sellers to receive the book quickly. Not only did I not receive it on time (as they guaranteed) but also when I contacted the customer service via chat to see what went down the representative was super rude and was NOT willing to help at all. She did not even bother to look into this issue and see what was happening and after me repeating the situation over and over again she is like, yes but it is what it is, it will come to you eventually and I cannot do anything. Basically I paid about 15-20$ more for nothing. Don’t waste your money by ordering this from amazon when you can get it cheaper from other seller and it almost takes almost the same amount of time.

⭐Theoretical Statistics contains an excellent smattering of interesting and useful topics in mathematical statistics and contains many exercises a good portion of which contain answers with explanations. As much as I want to like this book it simply contains too many superficial issues for me to give it a good review. Notation in the book is very sporadic too often assuming the definitions of variables from the context or from previous chapters; this is especially irritating for a book whose chapter topics tend to be very self-contained. These issues caused me to get hung up on stupid points for days (“oh lambda is equal to lambda_n even though it is mentioned nowhere”). Many of the explanations are unnecessarily difficult to follow and feel like they are written by someone with a good understanding of the subject who is unable to put himself in the mind of a person not familiar with the subject (an issue with many professors). Maybe the second version will be better.

⭐I similarly wanted to like this book – there are a lot of interesting topics, problems with solutions, and I was excited to get into it. Unfortunately it is very mediocre. The coverage of the topics is without motivation, clarity or much insight. In fact, I’ve rarely encountered books with so little insight into the material, it is more like a collection of facts. There are many typos, including in the solutions. The order of the topics isn’t particularly logical in my opinion. Perhaps if supplemented by really good lectures it would be ok, but I can’t recommend it.

⭐Require a solid background in linear algebra and calculus and a little exposure to statistical inference theory before reading this book. But the author’s explanation is so clear that you can read it with a lot of joy. Highly recommend to anyone who wants a rigorous training in theoretical statistics.

⭐The book covers all major statistics inference topics in a succinct, clear manner. The problem sets are quite helpful. It is used as the first year Ph.D. textbook. If you could think carefully about the details and Prof. Keener’s ideology, you will know how valuable this book is!

⭐just as described

⭐Pros:1) Provides a list of the topics that one should cover in a first year statistics PhD course.2) Provides solutions to some exercises, which is useful for study.Cons:1) As others have mentioned, it seems that Professor Keener is simply not able to put himself into the mind of an individual whom does not have a lucid understanding of this material. My professor loves this book even though all of his students constantly bemoan it. So it’s probably great if you’re already an expert in the material.2) There is not intuition or reasoning or exposition. The text babbles for pages and pages of dense material without any insight into why the material matters. Often, Keener will introduce a key theorem or result after he proves it. This creates a jarring narrative that’s impossible to follow.3) Chapter 7 is the biggest pile of garbage I’ve ever read in a textbook. I have no idea how anyone thought it was acceptable to publish this chapter. 2 pages of moving symbols around for no explained reason followed by several pages of hand-waived examples and then the strangest justification of the estimator risk as a metric I’ve ever seen.You’d be better off using a botany book to learn statistics.

Keywords

Free Download Theoretical Statistics: Topics for a Core Course (Springer Texts in Statistics) 2010th Edition in PDF format
Theoretical Statistics: Topics for a Core Course (Springer Texts in Statistics) 2010th Edition PDF Free Download
Download Theoretical Statistics: Topics for a Core Course (Springer Texts in Statistics) 2010th Edition 2010 PDF Free
Theoretical Statistics: Topics for a Core Course (Springer Texts in Statistics) 2010th Edition 2010 PDF Free Download
Download Theoretical Statistics: Topics for a Core Course (Springer Texts in Statistics) 2010th Edition PDF
Free Download Ebook Theoretical Statistics: Topics for a Core Course (Springer Texts in Statistics) 2010th Edition