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Nonparametric Methods in Change Point Problems, Brodsky, E., Darkhovsky, B.S.



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Цена: 9926р.
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Автор: Brodsky, E., Darkhovsky, B.S.
Название:  Nonparametric Methods in Change Point Problems   (Э.Бродски: Непараметрические методы изменения точечных задач)
Издательство: Springer
Классификация:
ISBN: 0792321227
ISBN-13(EAN): 9780792321224
Обложка/Формат: Hardback
Страницы: 224
Вес: 1.09 кг.
Дата издания: 1993
Серия: Mathematics and its applications
Язык: English
Размер: 247 x 168 x 19
Читательская аудитория: Professional & vocational
Ссылка на Издательство: Link
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Поставляется из: Германии
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.



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: 9926 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.

Nonlinear Time Series / Nonparametric and Parametric Methods

Автор: Fan Jianqing, Yao Qiwei
Название: Nonlinear Time Series / Nonparametric and Parametric Methods
ISBN: 0387261427 ISBN-13(EAN): 9780387261423
Издательство: Springer
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Цена: 11494 р.
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Описание: This book presents the contemporary statistical methods and theory of nonlinear time series analysis. The principal focus is on nonparametric and semiparametric techniques developed in the last decade. It covers the techniques for modelling in state-space, in frequency-domain as well as in time-domain. To reflect the integration of parametric and nonparametric methods in analyzing time series data, the book also presents an up-to-date exposure of some parametric nonlinear models, including ARCH/GARCH models and threshold models. A compact view on linear ARMA models is also provided. Data arising in real applications are used throughout to show how nonparametric approaches may help to reveal local structure in high-dimensional data. Important technical tools are also introduced. The book will be useful for graduate students, application-oriented time series analysts, and new and experienced researchers. It will have the value both within the statistical community and across a broad spectrum of other fields such as econometrics, empirical finance, population biology and ecology. The prerequisites are basic courses in probability and statistics. Jianqing Fan, coauthor of the highly regarded book Local Polynomial Modeling, is Professor of Statistics at the University of North Carolina at Chapel Hill and the Chinese University of Hong Kong. His published work on nonparametric modeling, nonlinear time series, financial econometrics, analysis of longitudinal data, model selection, wavelets and other aspects of methodological and theoretical statistics has been recognized with the Presidents' Award from the Committee of Presidents of Statistical Societies, the Hettleman Prize for Artistic and Scholarly Achievement from the University of North Carolina, and by his election as a fellow of the American Statistical Association and the Institute of Mathematical Statistics. Qiwei Yao is Professor of Statistics at the London School of Economics and Political Science. He is an elected member of the International Statistical Institute, and has served on the editorial boards for the Journal of the Royal Statistical Society (Series B) and the Australian and New Zealand Journal 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.

Robust Nonparametric Statistical Methods, Second Edition

Автор: Hettmansperger
Название: Robust Nonparametric Statistical Methods, Second Edition
ISBN: 1439809089 ISBN-13(EAN): 9781439809082
Издательство: Taylor&Francis
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Цена: 16170 р.
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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

Nonparametric Methods in Statistics with SAS Applications

Автор: Korosteleva
Название: Nonparametric Methods in Statistics with SAS Applications
ISBN: 1466580623 ISBN-13(EAN): 9781466580626
Издательство: Taylor&Francis
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Цена: 7275 р.
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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 Statistical Tests

Автор: Neuhauser
Название: Nonparametric Statistical Tests
ISBN: 1439867038 ISBN-13(EAN): 9781439867037
Издательство: Taylor&Francis
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Цена: 20790 р.
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Описание: Nonparametric Statistical Tests: A Computational Approach describes classical nonparametric tests, as well as novel and little-known methods such as the Baumgartner-Weiss-Schindler and the Cucconi tests. The book presents SAS and R programs, allowing readers to carry out the different statistical methods, such as permutation and bootstrap tests. The author considers example data sets in each chapter to illustrate methods. Numerous real-life data from various areas, including the bible, and their analyses provide for greatly diversified reading. The book covers: Nonparametric two-sample tests for the location-shift model, specifically the Fisher-Pitman permutation test, the Wilcoxon rank sum test, and the Baumgartner-Weiss-Schindler test Permutation tests, location-scale tests, tests for the nonparametric Behrens-Fisher problem, and tests for a difference in variability Tests for the general alternative, including the (Kolmogorov-)Smirnov test, ordered categorical, and discrete numerical data Well-known one-sample tests such as the sign test and Wilcoxon’s signed rank test, a modification suggested by Pratt (1959), a permutation test with original observations, and a one-sample bootstrap test are presented. Tests for more than two groups, the following tests are described in detail: the Kruskal-Wallis test, the permutation F test, the Jonckheere-Terpstra trend test, tests for umbrella alternatives, and the Friedman and Page tests for multiple dependent groups The concepts of independence and correlation, and stratified tests such as the van Elteren test and combination tests The applicability of computer-intensive methods such as bootstrap and permutation tests for non-standard situations and complex designs Although the major development of nonparametric methods came to a certain end in the 1970s, their importance undoubtedly persists. What is still needed is a computer assisted evaluation of their main properties. This book closes that gap.

Nonparametric Statistical Methods And Related Topics: A Festschrift In Honor Of Professor P K Bhattacharya On The Occasion Of His 80Th Birthday

Автор: Samaniego Francisco J Et Al
Название: Nonparametric Statistical Methods And Related Topics: A Festschrift In Honor Of Professor P K Bhattacharya On The Occasion Of His 80Th Birthday
ISBN: 9814366560 ISBN-13(EAN): 9789814366564
Издательство: World Scientific Publishing
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Цена: 13690 р.
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Описание: Consists of 22 research papers in Probability and Statistics. This title includes topics such as nonparametric inference, nonparametric curve fitting, linear model theory, Bayesian nonparametrics, change point problems, time series analysis and asymptotic theory. It presents research in statistical theory.

Nonparametric Simple Regression

Автор: Fox J
Название: Nonparametric Simple Regression
ISBN: 0761915850 ISBN-13(EAN): 9780761915850
Издательство: Sage Publications
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Цена: 2070 р.
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Описание: John Fox introduces readers to the techniques of kernel estimation, additive nonparametric regression, and the ways nonparametric regression can be employed to select transformations of the data preceding a linear least-squares fit.

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.
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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

Multivariate Nonparametric Methods with R

Автор: Oja Hannu
Название: Multivariate Nonparametric Methods with R
ISBN: 1441904670 ISBN-13(EAN): 9781441904676
Издательство: Springer
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Цена: 13584 р.
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Описание: Offers a fresh, fairly efficient, and robust alternative to analyzing multivariate data. This monograph provides an overview of the theory of multivariate nonparametric methods based on spatial signs and ranks. It uses marginal signs and ranks and different type of L1 norm.

Nonparametric Statistics for Social and Behavioral Sciences

Автор: Kraska-Miller
Название: Nonparametric Statistics for Social and Behavioral Sciences
ISBN: 1466507608 ISBN-13(EAN): 9781466507609
Издательство: Taylor&Francis
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Цена: 9239 р.
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Описание: Incorporating a hands-on pedagogical approach, Nonparametric Statistics for Social and Behavioral Sciences presents the concepts, principles, and methods used in performing many nonparametric procedures. It also demonstrates practical applications of the most common nonparametric procedures using IBM’s SPSS software. This text is the only current nonparametric book written specifically for students in the behavioral and social sciences. Emphasizing sound research designs, appropriate statistical analyses, and accurate interpretations of results, the text: Explains a conceptual framework for each statistical procedure Presents examples of relevant research problems, associated research questions, and hypotheses that precede each procedure Details SPSS paths for conducting various analyses Discusses the interpretations of statistical results and conclusions of the research With minimal coverage of formulas, the book takes a nonmathematical approach to nonparametric data analysis procedures and shows students how they are used in research contexts. Each chapter includes examples, exercises, and SPSS screen shots illustrating steps of the statistical procedures and resulting output.

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.


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