Introduction To Nonparametric Regression
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Introduction To Nonparametric Regression
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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.
Introduction To Nonparametric Estimation
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Author : Alexandre B. Tsybakov
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-10-22
Introduction To Nonparametric Estimation written by Alexandre B. Tsybakov 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 2008-10-22 with Mathematics categories.
Developed from lecture notes and ready to be used for a course on the graduate level, this concise text aims to introduce the fundamental concepts of nonparametric estimation theory while maintaining the exposition suitable for a first approach in the field.
Nonparametric Regression Analysis Of Longitudinal Data
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Author : Hans-Georg Müller
language : en
Publisher: Springer
Release Date : 1988-01-01
Nonparametric Regression Analysis Of Longitudinal Data written by Hans-Georg Müller and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 1988-01-01 with Longitudinal method categories.
An Introduction To Nonparametric Statistics
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Author : John E. Kolassa
language : en
Publisher: CRC Press
Release Date : 2020-09-28
An Introduction To Nonparametric Statistics written by John E. Kolassa and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-28 with Mathematics categories.
An Introduction to Nonparametric Statistics presents techniques for statistical analysis in the absence of strong assumptions about the distributions generating the data. Rank-based and resampling techniques are heavily represented, but robust techniques are considered as well. These techniques include one-sample testing and estimation, multi-sample testing and estimation, and regression. Attention is paid to the intellectual development of the field, with a thorough review of bibliographical references. Computational tools, in R and SAS, are developed and illustrated via examples. Exercises designed to reinforce examples are included. Features Rank-based techniques including sign, Kruskal-Wallis, Friedman, Mann-Whitney and Wilcoxon tests are presented Tests are inverted to produce estimates and confidence intervals Multivariate tests are explored Techniques reflecting the dependence of a response variable on explanatory variables are presented Density estimation is explored The bootstrap and jackknife are discussed This text is intended for a graduate student in applied statistics. The course is best taken after an introductory course in statistical methodology, elementary probability, and regression. Mathematical prerequisites include calculus through multivariate differentiation and integration, and, ideally, a course in matrix algebra.
A Distribution Free Theory Of Nonparametric Regression
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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.
Applied Nonparametric Regression
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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 And Semiparametric Models
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Author : Wolfgang Karl Härdle
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-08-27
Nonparametric And Semiparametric Models written by Wolfgang Karl Härdle 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 2012-08-27 with Mathematics categories.
The statistical and mathematical principles of smoothing with a focus on applicable techniques are presented in this book. It naturally splits into two parts: The first part is intended for undergraduate students majoring in mathematics, statistics, econometrics or biometrics whereas the second part is intended to be used by master and PhD students or researchers. The material is easy to accomplish since the e-book character of the text gives a maximum of flexibility in learning (and teaching) intensity.
Nonparametric Regression And Generalized Linear Models
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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 re
Nonparametric Statistics With Applications To Science And Engineering
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Author : Paul H. Kvam
language : en
Publisher: John Wiley & Sons
Release Date : 2007-08-24
Nonparametric Statistics With Applications To Science And Engineering written by Paul H. Kvam 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 2007-08-24 with Mathematics categories.
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 Science and Engineering begins with succinct coverage of basic results for order statistics, methods of categorical data analysis, nonparametric regression, and curve fitting methods. The authors then focus on nonparametric procedures that are becoming more relevant to engineering researchers and practitioners. The important fundamental materials needed to effectively learn and apply the discussed methods are also provided throughout the book. Complete with exercise sets, chapter reviews, and a related Web site that features downloadable MATLAB applications, this book is an essential textbook for graduate courses in engineering and the physical sciences and also serves as a valuable reference for researchers who seek a more comprehensive understanding of modern nonparametric statistical methods.
Nonparametric Regression Analysis Of Longitudinal Data
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Author : Hans-Georg Müller
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Nonparametric Regression Analysis Of Longitudinal Data written by Hans-Georg Müller 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 2012-12-06 with Mathematics categories.
This monograph reviews some of the work that has been done for longitudi nal data in the rapidly expanding field of nonparametric regression. The aim is to give the reader an impression of the basic mathematical tools that have been applied, and also to provide intuition about the methods and applications. Applications to the analysis of longitudinal studies are emphasized to encourage the non-specialist and applied statistician to try these methods out. To facilitate this, FORTRAN programs are provided which carry out some of the procedures described in the text. The emphasis of most research work so far has been on the theoretical aspects of nonparametric regression. It is my hope that these techniques will gain a firm place in the repertoire of applied statisticians who realize the large potential for convincing applications and the need to use these techniques concurrently with parametric regression. This text evolved during a set of lectures given by the author at the Division of Statistics at the University of California, Davis in Fall 1986 and is based on the author's Habilitationsschrift submitted to the University of Marburg in Spring 1985 as well as on published and unpublished work. Completeness is not attempted, neither in the text nor in the references. The following persons have been particularly generous in sharing research or giving advice: Th. Gasser, P. Ihm, Y. P. Mack, V. Mammi tzsch, G . G. Roussas, U. Stadtmuller, W. Stute and R.