All Of Statistics


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All Of Statistics

All Of Statistics Author by : Larry Wasserman
Languange Used : en
Release Date : 2013-12-11
Publisher by : Springer Science & Business Media
ISBN : 9780387217369
File Size : 43,8 Mb
Total Download : 301

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 i
Category: Mathematics

All Of Statistics

All Of Statistics Author by : Larry Wasserman
Languange Used : en
Release Date : 2004-09-17
Publisher by : Springer Science & Business Media
ISBN : 0387402721
File Size : 46,6 Mb
Total Download : 820

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.
Category: Computers

All Of Nonparametric Statistics

All Of Nonparametric Statistics Author by : Larry Wasserman
Languange Used : en
Release Date : 2006-09-10
Publisher by : Springer Science & Business Media
ISBN : 0387306234
File Size : 54,7 Mb
Total Download : 718

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 approac
Category: Mathematics
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