Topics In Nonparametric Statistics

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Topics In Nonparametric Statistics

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Author : Michael G. Akritas
language : en
Publisher:
Release Date : 2014-12-31

Topics In Nonparametric Statistics written by Michael G. Akritas and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-12-31 with categories.

Nonparametric Statistics And Related Topics

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Author :
language : en
Publisher:
Release Date : 1992

Nonparametric Statistics And Related Topics written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992 with Mathematical statistics categories.

Nonparametric Statistics And Related Topics

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Author : A. K. Md. Ehsanes Saleh
language : en
Publisher: Amsterdam : North-Holland ; New York : Distributors for the U.S. and Canada, Elsevier Science Publishing Company
Release Date : 1992

Nonparametric Statistics And Related Topics written by A. K. Md. Ehsanes Saleh and has been published by Amsterdam : North-Holland ; New York : Distributors for the U.S. and Canada, Elsevier Science Publishing Company this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992 with Mathematics categories.

Significant developments have taken place during the last thirty years in the field of nonparametric statistics and related topics. These developments and future directions are discussed in this book. Some of the developments focussed on include: robust statistics; rank estimation; bootstrap techniques; regression quantiles; strong approximation of quantile processes; and a preliminary test approach to estimation (combining robust statistics and shrinkage estimation).This volume is dedicated to the memory of Professor Wassily Hoeffding, a pioneer in the field of nonparametric statistics.

Topics In Nonparametric Statistics

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Author : Michael G. Akritas
language : en
Publisher: Springer
Release Date : 2014-12-02

Topics In Nonparametric Statistics written by Michael G. Akritas and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-12-02 with Mathematics categories.

This volume is composed of peer-reviewed papers that have developed from the First Conference of the International Society for Non Parametric Statistics (ISNPS). This inaugural conference took place in Chalkidiki, Greece, June 15-19, 2012. It was organized with the co-sponsorship of the IMS, the ISI and other organizations. M.G. Akritas, S.N. Lahiri and D.N. Politis are the first executive committee members of ISNPS and the editors of this volume. ISNPS has a distinguished Advisory Committee that includes Professors R.Beran, P.Bickel, R. Carroll, D. Cook, P. Hall, R. Johnson, B. Lindsay, E. Parzen, P. Robinson, M. Rosenblatt, G. Roussas, T. SubbaRao and G. Wahba. The Charting Committee of ISNPS consists of more than 50 prominent researchers from all over the world. The chapters in this volume bring forth recent advances and trends in several areas of nonparametric statistics. In this way, the volume facilitates the exchange of research ideas, promotes collaboration among researchers from all over the world and contributes to the further development of the field. The conference program included over 250 talks, including special invited talks, plenary talks and contributed talks on all areas of nonparametric statistics. Out of these talks, some of the most pertinent ones have been refereed and developed into chapters that share both research and developments in the field.

All Of Nonparametric Statistics

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Author : Larry Wasserman
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-09-10

All Of Nonparametric Statistics written by Larry Wasserman 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 2006-09-10 with Mathematics categories.

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.

Nonparametric Statistics For Non Statisticians

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Author : Gregory W. Corder
language : en
Publisher: John Wiley & Sons
Release Date : 2011-09-20

Nonparametric Statistics For Non Statisticians written by Gregory W. Corder 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 2011-09-20 with Mathematics categories.

A practical and understandable approach to nonparametric statistics for researchers across diverse areas of study As the importance of nonparametric methods in modern statistics continues to grow, these techniques are being increasingly applied to experimental designs across various fields of study. However, researchers are not always properly equipped with the knowledge to correctly apply these methods. Nonparametric Statistics for Non-Statisticians: A Step-by-Step Approach fills a void in the current literature by addressing nonparametric statistics in a manner that is easily accessible for readers with a background in the social, behavioral, biological, and physical sciences. Each chapter follows the same comprehensive format, beginning with a general introduction to the particular topic and a list of main learning objectives. A nonparametric procedure is then presented and accompanied by context-based examples that are outlined in a step-by-step fashion. Next, SPSS® screen captures are used to demonstrate how to perform and recognize the steps in the various procedures. Finally, the authors identify and briefly describe actual examples of corresponding nonparametric tests from diverse fields. Using this organized structure, the book outlines essential skills for the application of nonparametric statistical methods, including how to: Test data for normality and randomness Use the Wilcoxon signed rank test to compare two related samples Apply the Mann-Whitney U test to compare two unrelated samples Compare more than two related samples using the Friedman test Employ the Kruskal-Wallis H test to compare more than two unrelated samples Compare variables of ordinal or dichotomous scales Test for nominal scale data A detailed appendix provides guidance on inputting and analyzing the presented data using SPSS®, and supplemental tables of critical values are provided. In addition, the book's FTP site houses supplemental data sets and solutions for further practice. Extensively classroom tested, Nonparametric Statistics for Non-Statisticians is an ideal book for courses on nonparametric statistics at the upper-undergraduate and graduate levels. It is also an excellent reference for professionals and researchers in the social, behavioral, and health sciences who seek a review of nonparametric methods and relevant applications.

Topics In Nonparametric Statistics

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Author : Christopher Chang
language : en
Publisher:
Release Date : 2011

Topics In Nonparametric Statistics written by Christopher Chang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with categories.

This thesis is concerned with nonparametric techniques for inferring properties of time series. First, we consider finite-order moving average and nonlinear autoregressive processes with no parametric assumption on the innovation distribution, and present a kernel density estimator of a bootstrap series that estimates their marginal densities root-$n$ consistently. This is equal to the rate of the best known convolution estimators, and faster than the standard kernel density estimator. We also conduct simulations to check the finite sample properties of our estimator, and the results are generally better than corresponding results for the standard kernel density estimator. Next, given stationary time series data, we study the problem of finding the best linear combination of a set of lag window spectral density estimators with respect to the mean squared risk. We present an aggregation procedure and prove a sharp oracle inequality for its risk. We also provide simulations demonstrating the performance of our aggregation procedure, given Bartlett and other estimators of varying bandwidths as input. This extends work by Rigollet and Tsybakov on aggregation of density estimators. The last part of this thesis introduces a class of robust autocorrelation estimators based on interpreting the sample autocorrelation function as a linear regression. We investigate the efficiency and robustness properties of the estimators that result from plugging on three common robust regression techniques. Construction of robust autocovariance and positive definite autocorrelation estimates is discussed, as well as application of the estimators to AR model fitting. We finish with simulations, which suggest that the estimators are especially well suited for AR model fitting.

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 Statistical Methods

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Author : Myles Hollander
language : en
Publisher: John Wiley & Sons
Release Date : 2013-11-25

Nonparametric Statistical Methods written by Myles Hollander 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 2013-11-25 with Mathematics categories.

Praise for the Second Edition “This book should be an essential part of the personal library of every practicing statistician.”—Technometrics Thoroughly revised and updated, the new edition of Nonparametric Statistical Methods includes additional modern topics and procedures, more practical data sets, and new problems from real-life situations. The book continues to emphasize the importance of nonparametric methods as a significant branch of modern statistics and equips readers with the conceptual and technical skills necessary to select and apply the appropriate procedures for any given situation. Written by leading statisticians, Nonparametric Statistical Methods, Third Edition provides readers with crucial nonparametric techniques in a variety of settings, emphasizing the assumptions underlying the methods. The book provides an extensive array of examples that clearly illustrate how to use nonparametric approaches for handling one- or two-sample location and dispersion problems, dichotomous data, and one-way and two-way layout problems. In addition, the Third Edition features: The use of the freely available R software to aid in computation and simulation, including many new R programs written explicitly for this new edition New chapters that address density estimation, wavelets, smoothing, ranked set sampling, and Bayesian nonparametrics Problems that illustrate examples from agricultural science, astronomy, biology, criminology, education, engineering, environmental science, geology, home economics, medicine, oceanography, physics, psychology, sociology, and space science Nonparametric Statistical Methods, Third Edition is an excellent reference for applied statisticians and practitioners who seek a review of nonparametric methods and their relevant applications. The book is also an ideal textbook for upper-undergraduate and first-year graduate courses in applied nonparametric statistics.

Nonparametric Statistics

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Author : Michele La Rocca
language : en
Publisher: Springer Nature
Release Date : 2020-11-11

Nonparametric Statistics written by Michele La Rocca and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-11 with Mathematics categories.

Highlighting the latest advances in nonparametric and semiparametric statistics, this book gathers selected peer-reviewed contributions presented at the 4th Conference of the International Society for Nonparametric Statistics (ISNPS), held in Salerno, Italy, on June 11-15, 2018. It covers theory, methodology, applications and computational aspects, addressing topics such as nonparametric curve estimation, regression smoothing, models for time series and more generally dependent data, varying coefficient models, symmetry testing, robust estimation, and rank-based methods for factorial design. It also discusses nonparametric and permutation solutions for several different types of data, including ordinal data, spatial data, survival data and the joint modeling of both longitudinal and time-to-event data, permutation and resampling techniques, and practical applications of nonparametric statistics. The International Society for Nonparametric Statistics is a unique global organization, and its international conferences are intended to foster the exchange of ideas and the latest advances and trends among researchers from around the world and to develop and disseminate nonparametric statistics knowledge. The ISNPS 2018 conference in Salerno was organized with the support of the American Statistical Association, the Institute of Mathematical Statistics, the Bernoulli Society for Mathematical Statistics and Probability, the Journal of Nonparametric Statistics and the University of Salerno.