Nonparametric Simple Regression
DOWNLOAD
Download Nonparametric Simple Regression PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Nonparametric Simple Regression book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Nonparametric Simple Regression
DOWNLOAD
Author : John Fox
language : en
Publisher: SAGE
Release Date : 2000-01-20
Nonparametric Simple Regression written by John Fox and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-01-20 with Social Science categories.
Nonparametric simple regression forms the basis for nonparametric multiple regression and directly supplies the building blocks for the type of nonparametric multiple regression called additive regression.
Nonparametric Regression And Generalized Linear Models
DOWNLOAD
Author : P.J. Green
language : en
Publisher: CRC Press
Release Date : 1993-05-01
Nonparametric Regression And Generalized Linear Models written by P.J. Green and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993-05-01 with Mathematics categories.
In recent years, there has been a great deal of interest and activity in the general area of nonparametric smoothing in statistics. This monograph concentrates on the roughness penalty method and shows how this technique provides a unifying approach to a wide range of smoothing problems. The method allows parametric assumptions to be realized in regression problems, in those approached by generalized linear modelling, and in many other contexts. The emphasis throughout is methodological rather than theoretical, and it concentrates on statistical and computation issues. Real data examples are used to illustrate the various methods and to compare them with standard parametric approaches. Some publicly available software is also discussed. The mathematical treatment is self-contained and depends mainly on simple linear algebra and calculus. This monograph will be useful both as a reference work for research and applied statisticians and as a text for graduate students and other encountering the material for the first time.
Multiple And Generalized Nonparametric Regression
DOWNLOAD
Author : John Fox
language : en
Publisher: SAGE Publications
Release Date : 2000-05-01
Multiple And Generalized Nonparametric Regression written by John Fox and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-05-01 with Social Science categories.
This book builds on John Fox's previous volume in the QASS Series, Non Parametric Simple Regression. In this book, the reader learns how to estimate and plot smooth functions when there are multiple independent variables.
Nonparametric Regression And Spline Smoothing Second Edition
DOWNLOAD
Author : Randall L. Eubank
language : en
Publisher: CRC Press
Release Date : 1999-02-09
Nonparametric Regression And Spline Smoothing Second Edition written by Randall L. Eubank and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999-02-09 with Mathematics categories.
Provides a unified account of the most popular approaches to nonparametric regression smoothing. This edition contains discussions of boundary corrections for trigonometric series estimators; detailed asymptotics for polynomial regression; testing goodness-of-fit; estimation in partially linear models; practical aspects, problems and methods for confidence intervals and bands; local polynomial regression; and form and asymptotic properties of linear smoothing splines.
Introduction To Nonparametric Regression
DOWNLOAD
Author : K. Takezawa
language : en
Publisher: John Wiley & Sons
Release Date : 2005-12-02
Introduction To Nonparametric Regression written by K. Takezawa and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-12-02 with Mathematics categories.
An easy-to-grasp introduction to nonparametric regression This book's straightforward, step-by-step approach provides an excellent introduction to the field for novices of nonparametric regression. Introduction to Nonparametric Regression clearly explains the basic concepts underlying nonparametric regression and features: * Thorough explanations of various techniques, which avoid complex mathematics and excessive abstract theory to help readers intuitively grasp the value of nonparametric regression methods * Statistical techniques accompanied by clear numerical examples that further assist readers in developing and implementing their own solutions * Mathematical equations that are accompanied by a clear explanation of how the equation was derived The first chapter leads with a compelling argument for studying nonparametric regression and sets the stage for more advanced discussions. In addition to covering standard topics, such as kernel and spline methods, the book provides in-depth coverage of the smoothing of histograms, a topic generally not covered in comparable texts. With a learning-by-doing approach, each topical chapter includes thorough S-Plus? examples that allow readers to duplicate the same results described in the chapter. A separate appendix is devoted to the conversion of S-Plus objects to R objects. In addition, each chapter ends with a set of problems that test readers' grasp of key concepts and techniques and also prepares them for more advanced topics. This book is recommended as a textbook for undergraduate and graduate courses in nonparametric regression. Only a basic knowledge of linear algebra and statistics is required. In addition, this is an excellent resource for researchers and engineers in such fields as pattern recognition, speech understanding, and data mining. Practitioners who rely on nonparametric regression for analyzing data in the physical, biological, and social sciences, as well as in finance and economics, will find this an unparalleled resource.
A Distribution Free Theory Of Nonparametric Regression
DOWNLOAD
Author : László Györfi
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-04-18
A Distribution Free Theory Of Nonparametric Regression written by László Györfi and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-04-18 with Mathematics categories.
This book provides a systematic in-depth analysis of nonparametric regression with random design. It covers almost all known estimates. The emphasis is on distribution-free properties of the estimates.
Spline Smoothing And Nonparametric Regression
DOWNLOAD
Author : Randall L. Eubank
language : en
Publisher:
Release Date : 1988
Spline Smoothing And Nonparametric Regression written by Randall L. Eubank and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1988 with Mathematics categories.
Regression analysis; Nonparametric regression; Scope; What is a good estimator? Function spaces and series estimators; Kernel estimators; Smoothing splines; Smoothing splines: extensions and asymptotic theory; Least-squares splines and other estimators; Linear and nonlinear regression; Linear models; Nonlinear models; Bayesian interpretations and inference.
Semiparametric Regression
DOWNLOAD
Author : David Ruppert
language : en
Publisher: Cambridge University Press
Release Date : 2003-07-14
Semiparametric Regression written by David Ruppert and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-07-14 with Mathematics categories.
Even experts on semiparametric regression should find something new here.
Applied Nonparametric Regression
DOWNLOAD
Author : Wolfgang Härdle
language : en
Publisher: Cambridge University Press
Release Date : 1990
Applied Nonparametric Regression written by Wolfgang Härdle and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1990 with Business & Economics categories.
This is the first book to bring together in one place the techniques for regression curve smoothing involving more than one variable.
Nonparametric Statistical Methods Using R
DOWNLOAD
Author : John Kloke
language : en
Publisher: CRC Press
Release Date : 2014-10-09
Nonparametric Statistical Methods Using R written by John Kloke and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-10-09 with Mathematics categories.
A Practical Guide to Implementing Nonparametric and Rank-Based Procedures Nonparametric Statistical Methods Using R covers traditional nonparametric methods and rank-based analyses, including estimation and inference for models ranging from simple location models to general linear and nonlinear models for uncorrelated and correlated responses. The authors emphasize applications and statistical computation. They illustrate the methods with many real and simulated data examples using R, including the packages Rfit and npsm. The book first gives an overview of the R language and basic statistical concepts before discussing nonparametrics. It presents rank-based methods for one- and two-sample problems, procedures for regression models, computation for general fixed-effects ANOVA and ANCOVA models, and time-to-event analyses. The last two chapters cover more advanced material, including high breakdown fits for general regression models and rank-based inference for cluster correlated data. The book can be used as a primary text or supplement in a course on applied nonparametric or robust procedures and as a reference for researchers who need to implement nonparametric and rank-based methods in practice. Through numerous examples, it shows readers how to apply these methods using R.