all of statistics a concise course in statistical inference springer texts in statistics

Download Book All Of Statistics A Concise Course In Statistical Inference Springer Texts In Statistics in PDF format. You can Read Online All Of Statistics A Concise Course In Statistical Inference Springer Texts In Statistics here in PDF, EPUB, Mobi or Docx formats.

All Of Statistics

Author : Larry Wasserman
ISBN : 9780387217369
Genre : Mathematics
File Size : 42. 9 MB
Format : PDF, ePub
Download : 217
Read : 1026

Download Now


Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like non-parametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analysing data.

All Of Statistics

Author : Larry Wasserman
ISBN : 0387402721
Genre : Computers
File Size : 41. 57 MB
Format : PDF, Docs
Download : 858
Read : 1183

Download Now


This book surveys a broad range of topics in probability and mathematical statistics. It provides the statistical background that a computer scientist needs to work in the area of machine learning.

All Of Statistics

Author : Larry Wasserman
ISBN : 1468495526
Genre :
File Size : 62. 28 MB
Format : PDF, Docs
Download : 692
Read : 1001

Download Now



All Of Nonparametric Statistics

Author : Larry Wasserman
ISBN : 0387306234
Genre : Mathematics
File Size : 63. 28 MB
Format : PDF, ePub, Mobi
Download : 167
Read : 1208

Download Now


This text provides the reader with a single book where they can find accounts of a number of up-to-date issues in nonparametric inference. The book is aimed at Masters or PhD level students in statistics, computer science, and engineering. It is also suitable for researchers who want to get up to speed quickly on modern nonparametric methods. It covers a wide range of topics including the bootstrap, the nonparametric delta method, nonparametric regression, density estimation, orthogonal function methods, minimax estimation, nonparametric confidence sets, and wavelets. The book’s dual approach includes a mixture of methodology and theory.

A Modern Introduction To Probability And Statistics

Author : F.M. Dekking
ISBN : 9781846281686
Genre : Mathematics
File Size : 28. 78 MB
Format : PDF, ePub, Mobi
Download : 968
Read : 849

Download Now


Suitable for self study Use real examples and real data sets that will be familiar to the audience Introduction to the bootstrap is included – this is a modern method missing in many other books

Theoretical Statistics

Author : Robert W. Keener
ISBN : 0387938397
Genre : Mathematics
File Size : 83. 63 MB
Format : PDF, Mobi
Download : 148
Read : 707

Download Now


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.

Essential Statistical Inference

Author : Dennis D. Boos
ISBN : 9781461448181
Genre : Mathematics
File Size : 88. 65 MB
Format : PDF, Docs
Download : 915
Read : 749

Download Now


​This book is for students and researchers who have had a first year graduate level mathematical statistics course. It covers classical likelihood, Bayesian, and permutation inference; an introduction to basic asymptotic distribution theory; and modern topics like M-estimation, the jackknife, and the bootstrap. R code is woven throughout the text, and there are a large number of examples and problems. An important goal has been to make the topics accessible to a wide audience, with little overt reliance on measure theory. A typical semester course consists of Chapters 1-6 (likelihood-based estimation and testing, Bayesian inference, basic asymptotic results) plus selections from M-estimation and related testing and resampling methodology. Dennis Boos and Len Stefanski are professors in the Department of Statistics at North Carolina State. Their research has been eclectic, often with a robustness angle, although Stefanski is also known for research concentrated on measurement error, including a co-authored book on non-linear measurement error models. In recent years the authors have jointly worked on variable selection methods. ​

Top Download:

Best Books