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Nonparametric Methods in Statistics with SAS Applications, Korosteleva



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Автор: Korosteleva
Название:  Nonparametric Methods in Statistics with SAS Applications
Издательство: Taylor&Francis
Классификация:
ISBN: 1466580623
ISBN-13(EAN): 9781466580626
Обложка/Формат: Paperback
Страницы: 195
Вес: 0.35 кг.
Дата издания: 18.09.2013
Серия: Chapman & hall/crc texts in statistical science
Язык: English
Иллюстрации: 68 tables, black and white; 22 illustrations, black and white
Размер: 233 x 156 x 12
Читательская аудитория: Tertiary education (us: college)
Ключевые слова: Probability & statistics, MATHEMATICS / Probability & Statistics / General
Основная тема: Statistical Theory & Methods
Ссылка на Издательство: Link
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Поставляется из: Англии
Описание: Designed for a graduate course in applied statistics, Nonparametric Methods in Statistics with SAS Applications teaches students how to apply nonparametric techniques to statistical data. It starts with the tests of hypotheses and moves on to regression modeling, time-to-event analysis, density estimation, and resampling methods. The text begins with classical nonparametric hypotheses testing, including the sign, Wilcoxon sign-rank and rank-sum, Ansari-Bradley, Kolmogorov-Smirnov, Friedman rank, Kruskal-Wallis H, Spearman rank correlation coefficient, and Fisher exact tests. It then discusses smoothing techniques (loess and thin-plate splines) for classical nonparametric regression as well as binary logistic and Poisson models. The author also describes time-to-event nonparametric estimation methods, such as the Kaplan-Meier survival curve and Cox proportional hazards model, and presents histogram and kernel density estimation methods. The book concludes with the basics of jackknife and bootstrap interval estimation. Drawing on data sets from the author’s many consulting projects, this classroom-tested book includes various examples from psychology, education, clinical trials, and other areas. It also presents a set of exercises at the end of each chapter. All examples and exercises require the use of SAS 9.3 software. Complete SAS codes for all examples are given in the text. Large data sets for the exercises are available on the author’s website.



Nonparametric Statistics with Applications to Science and Engineering

Автор: Kvam
Название: Nonparametric Statistics with Applications to Science and Engineering
ISBN: 0470081473 ISBN-13(EAN): 9780470081471
Издательство: Wiley
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Цена: 15015 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: 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.

Nonparametric Monte Carlo Tests and Their Applications

Автор: Zhu Lixing
Название: Nonparametric Monte Carlo Tests and Their Applications
ISBN: 0387250387 ISBN-13(EAN): 9780387250380
Издательство: Springer
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Цена: 8359 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: A fundamental issue in statistical analysis is testing the fit of a particular probability model to a set of observed data. Monte Carlo approximation to the null distribution of the test provides a convenient and powerful means of testing model fit. Nonparametric Monte Carlo Tests and Their Applications proposes a new Monte Carlo-based methodology to construct this type of approximation when the model is semistructured. When there are no nuisance parameters to be estimated, the nonparametric Monte Carlo test can exactly maintain the significance level, and when nuisance parameters exist, this method can allow the test to asymptotically maintain the level. The author addresses both applied and theoretical aspects of nonparametric Monte Carlo tests. The new methodology has been used for model checking in many fields of statistics, such as multivariate distribution theory, parametric and semiparametric regression models, multivariate regression models, varying-coefficient models with longitudinal data, heteroscedasticity, and homogeneity of covariance matrices. This book will be of interest to both practitioners and researchers investigating goodness-of-fit tests and resampling approximations.Every chapter of the book includes algorithms, simulations, and theoretical deductions. The prerequisites for a full appreciation of the book are a modest knowledge of mathematical statistics and limit theorems in probability/empirical process theory. The less mathematically sophisticated reader will find Chapters 1, 2 and 6 to be a comprehensible introduction on how and where the new method can apply and the rest of the book to be a valuable reference for Monte Carlo test approximation and goodness-of-fit tests.Lixing Zhu is Associate Professor of Statistics at the University of Hong Kong. He is a winner of the Humboldt Research Award at Alexander-von Humboldt Foundation of Germany and an elected Fellow of the Institute of Mathematical Statistics.From the reviews:"These lecture notes discuss several topics in goodness-of-fit testing, a classical area in statistical analysis. … The mathematical part contains detailed proofs of the theoretical results. Simulation studies illustrate the quality of the Monte Carlo approximation. … this book constitutes a recommendable contribution to an active area of current research." Winfried Stute for Mathematical Reviews, Issue 2006"...Overall, this is an interesting book, which gives a nice introduction to this new and specific field of resampling methods." Dongsheng Tu for Biometrics, September 2006

Nonparametric Statistics

Автор: Cao
Название: Nonparametric Statistics
ISBN: 3319415816 ISBN-13(EAN): 9783319415819
Издательство: Springer
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Цена: 11494 р.
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Описание: This volume collects selected, peer-reviewed contributions from the 2nd Conference of the International Society for Nonparametric Statistics (ISNPS), held in C?diz (Spain) between June 11–16 2014, and sponsored by the American Statistical Association, the Institute of Mathematical Statistics, the Bernoulli Society for Mathematical Statistics and Probability, the Journal of Nonparametric Statistics and Universidad Carlos III de Madrid.The 15 articles are a representative sample of the 336 contributed papers presented at the conference. They cover topics such as high-dimensional data modelling, inference for stochastic processes and for dependent data, nonparametric and goodness-of-fit testing, nonparametric curve estimation, object-oriented data analysis, and semiparametric inference.The aim of the ISNPS 2014 conference was to bring together recent advances and trends in several areas of nonparametric statistics in order to facilitate the exchange of research ideas, promote collaboration among researchers from around the globe, and contribute to the further development of the field.

Practical Nonparametric and Semiparametric Bayesian Statistics

Автор: Dey
Название: Practical Nonparametric and Semiparametric Bayesian Statistics
ISBN: 0387985174 ISBN-13(EAN): 9780387985176
Издательство: Springer
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Цена: 17241 р.
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Описание: Nonparametric and semiparametric statistical methods are attractive to researchers in a large number of fields, including pharmaceuticals, medical and public health centers, financial institutions, and environmental monitoring centers. This volume presents both the theoretical and applied aspects of these methods.

Nonparametric Statistical Methods

Автор: Hollander Myles
Название: Nonparametric Statistical Methods
ISBN: 0470387378 ISBN-13(EAN): 9780470387375
Издательство: Wiley
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Цена: 12128 р.
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Описание: Written by leading statisticians, this new edition has been completely updated to include additional modern topics and procedures, more real-world data sets, and more problems from real-life situations.

Nonparametric Methods in Change Point Problems

Автор: Brodsky, E., Darkhovsky, B.S.
Название: Nonparametric Methods in Change Point Problems
ISBN: 0792321227 ISBN-13(EAN): 9780792321224
Издательство: Springer
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Цена: 9926 р.
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Описание: This volume deals with non-parametric methods of change point (disorder) detection in random processes and fields. A systematic account is given of up-to-date developments in this rapidly evolving branch of statistics.

Applied Nonparametric Statistical Methods, Fourth Edition

Автор: Sprent
Название: Applied Nonparametric Statistical Methods, Fourth Edition
ISBN: 158488701X ISBN-13(EAN): 9781584887010
Издательство: Taylor&Francis
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Цена: 10394 р.
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Описание: While preserving the clear, accessible style of previous editions, this fourth edition reflects the latest developments in computer-intensive methods that deal with intractable analytical problems and unwieldy data sets. This edition summarizes relevant general statistical concepts and introduces basic ideas of nonparametric or distribution-free methods. Designed experiments, including those with factorial treatment structures, are now the focus of an entire chapter. The book also expands coverage on the analysis of survival data and the bootstrap method. The new final chapter focuses on important modern developments. With numerous exercises, the text offers the student edition of StatXact at a discounted price.

Nonparametric Statistics for Non-Statisticians

Автор: Corder Gregory W
Название: Nonparametric Statistics for Non-Statisticians
ISBN: 047045461X ISBN-13(EAN): 9780470454619
Издательство: Wiley
Рейтинг:
Цена: 6578 р.
Наличие на складе: Нет в наличии.

Описание: 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.

Introduction to Nonparametric Statistics for the Biological Sciences Using R

Автор: MacFarland
Название: Introduction to Nonparametric Statistics for the Biological Sciences Using R
ISBN: 3319306332 ISBN-13(EAN): 9783319306339
Издательство: Springer
Рейтинг:
Цена: 7000 р.
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Описание: This book contains a rich set of tools for nonparametric analyses, and the purpose of this supplemental text is to provide guidance to students and professional researchers onhow R is used for nonparametric data analysis in the biological sciences:To introduce when nonparametricapproaches to data analysis are appropriateTo introduce the leadingnonparametric tests commonly used in biostatistics and how R is used togenerate appropriate statistics for each testTo introduce common figurestypically associated with nonparametric data analysis and how R is used togenerate appropriate figures in support of each data setThe book focuses on how R is used todistinguish between data that could be classified as nonparametric as opposedto data that could be classified as parametric, with both approaches to data classification covered extensively.Following an introductory lesson on nonparametric statistics for the biological sciences, the book is organized into eight self-contained lessons on various analyses and tests using R to broadly compare differences between data sets and statistical approach.This supplemental text is intended for:Upper-level undergraduate and graduate students majoring in the biological sciences, specifically those in agriculture, biology, and health science - both students in lecture-type courses and also those engaged in research projects, such as a master's thesis or a doctoral dissertationAnd biological researchers at the professional level without a nonparametric statistics background but who regularly work with data more suitable to a nonparametric approach to data analysis

Recent Advances and Trends in Nonparametric Statistics,

Автор: M.G. Akritas
Название: Recent Advances and Trends in Nonparametric Statistics,
ISBN: 0444513787 ISBN-13(EAN): 9780444513786
Издательство: Elsevier Science
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Цена: 11495 р.
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Описание: Presents a collection of short articles - most of which having a review component - describing the developments of Nonparametric Statistics. This work includes topics such as: algorithic approaches; wavelets and nonlinear smoothers; graphical methods and data mining; biostatistics and bioinformatics; bagging and boosting; and more.

Practical Nonparametric Statistics

Автор: Conover, W.J.
Название: Practical Nonparametric Statistics
ISBN: 0471160687 ISBN-13(EAN): 9780471160687
Издательство: Wiley
Рейтинг:
Цена: 23100 р.
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Описание: This text aims to serve as a quick reference book offering instructions on how and when to use the most popular nonparametric procedures. It features procedures such as the Fisher Exact Test for two-by-two contingency tables, and the Mantel-Haenszel Test for combining several contingency tables.

Robust Nonparametric Statistical Methods, Second Edition

Автор: Hettmansperger
Название: Robust Nonparametric Statistical Methods, Second Edition
ISBN: 1439809089 ISBN-13(EAN): 9781439809082
Издательство: Taylor&Francis
Рейтинг:
Цена: 16170 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Presenting an extensive set of tools and methods for data analysis, this second edition includes more models and methods and significantly extends the possible analyses based on ranks. It contains a new section on rank procedures for nonlinear models, a new chapter on models with dependent error structure, and new material on the development of computationally efficient affine invariant/equivariant sign methods based on transform-retransform techniques in multivariate models. The authors illustrate the methods using many real-world examples and R. Information about the data sets and R packages can be found at www.crcpress.com


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