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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:
Психология
Вероятность и статистика
Математическое и статистическое программное обеспечение

ISBN: 1466580623
ISBN-13(EAN): 9781466580626
ISBN: 1-466-58062-3
ISBN-13(EAN): 978-1-466-58062-6
Обложка/Формат: Paperback
Страницы: 195
Вес: 0.35 кг.
Дата издания: 18.09.2013
Серия: Chapman & hall/crc texts in statistical science
Язык: ENG
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.
Дополнительное описание:




Introduction to Nonparametric Estimation

Автор: Alexandre B. Tsybakov
Название: Introduction to Nonparametric Estimation
ISBN: 0387790519 ISBN-13(EAN): 9780387790510
Издательство: Springer
Рейтинг:
Цена: 10284 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Presents basic nonparametric regression and density estimators and analyzes their properties. This book covers minimax lower bounds, and develops advanced topics such as: Pinsker`s theorem, oracle inequalities, Stein shrinkage, and sharp minimax adaptivity.

Nonparametric Techniques in Statistical Inference

Автор: Puri
Название: Nonparametric Techniques in Statistical Inference
ISBN: 0521093058 ISBN-13(EAN): 9780521093057
Издательство: Cambridge Academ
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Цена: 4579 р.
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Описание: Nonparametric techniques in statistics are those in which the data are ranked in order according to some particular characteristic. When applied to measurable characteristics, the use of such techniques often saves considerable calculation as compared with more formal methods, with only slight loss of accuracy. The field of nonparametric statistics is occupying an increasingly important role in statistical theory as well as in its applications. Nonparametric methods are mathematically elegant, and they also yield significantly improved performances in applications to agriculture, education, biometrics, medicine, communication, economics and industry.

Asymptotic Efficiency of Nonparametric Tests

Автор: Nikitin
Название: Asymptotic Efficiency of Nonparametric Tests
ISBN: 0521115922 ISBN-13(EAN): 9780521115926
Издательство: Cambridge Academ
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Цена: 2913 р.
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Описание: Making a substantiated choice of the most efficient statistical test is one of the basic problems of statistics. Asymptotic efficiency is an indispensable technique for comparing and ordering statistical tests in large samples. It is especially useful in nonparametric statistics where it is usually necessary to rely on heuristic tests. This monograph presents a unified treatment of the analysis and calculation of the asymptotic efficiencies of nonparametric tests. Powerful new methods are developed to evaluate explicitly different kinds of efficiencies. Of particular interest is the description of domains of the Bahadur local optimality and related characterisation problems based on recent research by the author. Other Russian results are also published here for the first time in English. Researchers, professionals and students in statistics will find this book invaluable.

Nonparametric Statistics

Автор: Cao
Название: Nonparametric Statistics
ISBN: 3319415816 ISBN-13(EAN): 9783319415819
Издательство: Springer
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Цена: 10284 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.

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: 13585 р.
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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.

Deconvolution Problems in Nonparametric Statistics

Автор: Alexander Meister
Название: Deconvolution Problems in Nonparametric Statistics
ISBN: 3540875565 ISBN-13(EAN): 9783540875567
Издательство: Springer
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Цена: 8882 р.
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Описание: Gives an introduction to deconvolution problems in nonparametric statistics. This title focuses on methodology (description of the estimation procedures) and theory (minimax convergence rates). It provides an appendix chapter on further results of Fourier analysis.

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: 5951 р.
Наличие на складе: Поставка под заказ.

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.

Practical Nonparametric and Semiparametric Bayesian Statistics

Автор: Dey
Название: Practical Nonparametric and Semiparametric Bayesian Statistics
ISBN: 0387985174 ISBN-13(EAN): 9780387985176
Издательство: Springer
Рейтинг:
Цена: 15427 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

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.

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: 10285 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.

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
Рейтинг:
Цена: 8882 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
Рейтинг:
Цена: 8150 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

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 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
Рейтинг:
Цена: 7479 р.
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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


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