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Author by : Larry Wasserman Languange Used : en Release Date : 2006-09-10 Publisher by : Springer Science & Business Media ISBN : 0387306234 File Size : 43,6 Mb Total Download : 512
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
Author by : Larry Wasserman Languange Used : en Release Date : 2013-12-11 Publisher by : Springer Science & Business Media ISBN : 9780387217369 File Size : 48,8 Mb Total Download : 502
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
Author by : Paul H. Kvam Languange Used : en Release Date : 2007-08-24 Publisher by : John Wiley & Sons ISBN : 0470168692 File Size : 51,6 Mb Total Download : 804
A thorough and definitive book that fully addresses traditional and modern-day topics of nonparametric statistics This book presents a practical approach to nonparametric statistical analysis and provides comprehensive coverage of both established and newly developed methods. With the use of MATLAB, the authors present information on theorems and rank tests in an applied fashion, with an emphasis on modern methods in regression and curve fitting, bootstrap confidence intervals, splines, wavelets, empirical likelihood, and goodness-of-fit testing. Nonparametric Statistics with Applications to S