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Tuesday, July 28, 2020 | History

3 edition of Robustness of statistical methods and nonparametric statistics found in the catalog.

Robustness of statistical methods and nonparametric statistics

Robustness of statistical methods and nonparametric statistics

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  • 2 Currently reading

Published by D. Reidel, Distributors for the U.S.A. and Canada, Kluwer Academic Publishers in Dordrecht, Boston, Hingham, MA, U.S.A .
Written in English

    Subjects:
  • Robust statistics.,
  • Nonparametric statistics.

  • Edition Notes

    Statementedited by Dieter Rasch and Moti Lal Tiku.
    SeriesTheory and decision library.
    ContributionsRasch, Dieter., Tiku, Moti Lal., Mathematische Gesellschaft der DDR., Conference on Robustness of Statistical Methods and Nonparametric Statistics (1983 : Schwerin, Germany)
    Classifications
    LC ClassificationsQA276.16 .R63 1984b
    The Physical Object
    Pagination172 p. :
    Number of Pages172
    ID Numbers
    Open LibraryOL2537404M
    ISBN 109027720762
    LC Control Number85018286

    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. Preface xiii. 1. Besides robust procedures, Dr. McKean has published in the areas of generalized linear models, nonparametric statistics and time series analyses. He has recently published articles on rank-based procedures for nonlinear, mixed, and GEE models. He is a co-author (with T.P. Hettmansperger) of the monograph Robust Nonparametric Statistical Methods.

    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 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.

      Besides robust procedures, Dr. McKean has published in the areas of generalized linear models, nonparametric statistics and time series analyses. He has recently published articles on rank-based procedures for nonlinear, mixed, and GEE models. He is a co-author (with T.P. Hettmansperger) of the monograph Robust Nonparametric Statistical Methods. The volume is dedicated to Hannu Oja on the occasion of his 65th birthday and is intended for researchers as well as PhD students with a good knowledge of statistics. Keywords 62H10, 62H12, 62H15, 62H20, 62G10, 62G35, 92C55 asymptotics dimension reduction multivariate statistics nonparametric statistical methods robustness.


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Robustness of statistical methods and nonparametric statistics Download PDF EPUB FB2

Robustness of Statistical Methods and Nonparametric Statistics. Editors (view affiliations) Dieter Rasch; Moti Lal Tiku; Search within book.

Front Matter. Pages i PDF. Robustness of Many-One Statistics. Eberhard Rudolph. Pages This volume contains most of the invited and contributed papers presented at the Conference on Robustness of Statistical Methods and Nonparametric Statistics held in the castle oj'Schwerin, Mai 29 - June 4 This conference was organized by the Mathematical Society of the GDR in cooperation with the Society of Physical and Mathematical.

Hettmansperger and McKean examine a wealth of interesting problems in connection with applying nonparametric robust methods. this is a well-written and nicely presented book that is likely to appeal to a reader with a good mathematical background and an interest in robust and nonparametric statistical by: Robustness of Statistical Methods and Nonparametric Statistics.

Editors: Rasch, Dieter, Tiku, Moti Lal (Eds.) Free PreviewBrand: Springer Netherlands. A statistical method is called non-parametric if it makes no assumption on the population distribution or sample size. This is in contrast with most parametric methods in elementary statistics. Robustness of Statistical Methods and Nonparametric Statistics by Dieter Rasch,available at Book Depository with free delivery worldwide.

COVID Resources. Reliable information about the coronavirus (COVID) is available from the World Health Organization (current situation, international travel).Numerous and frequently-updated resource results are available from this ’s WebJunction has pulled together information and resources to assist library staff as they consider how to handle coronavirus.

The robustness of parame tric statistical methods The test statistics t 1, t 2, and t 3 of the thre e tests can be found in the reference, test 1 was based on the original WALD-test. It will certainly become a standard reference for nonparametric and robust methods.

I recommend the book as an important textbook for research libraries. The book will soon find its place on the shelves and the tables of many kind of researchers and will serve as a graduate course textbook.

—Hannu Oja, International Statistical Review ( Joseph W. McKean is a professor of statistics at Western Michigan University. He has co-authored several books and published many papers on nonpara-metric and robust statistical procedures.

He is a fellow of the American Statisti - cal Association. Statistics The R Series Nonparametric Statistical Methods Using R John Kloke Joseph W.

McKean. The robustness of parametric statistical methods DIETER RASCH1, VOLKER GUIARD2 1. Abstract In psychological research sometimes non-parametric procedures are in use in cases, where the corresponding parametric procedure is preferable. This is mainly due to the fact. For robust nonparametric hypothesis tests of regression coefficients, the W (Wald) test statistic proposed by DiCiccio and Romano () should be preferred.

In this study, the permutation strategy of Huh and Jhun () was found to provide the best control of the type I error, but all permutation methods, except that of Still and White (   There are a few divisions of topics in statistics.

One division that quickly comes to mind is the differentiation between descriptive and inferential statistics. There are other ways that we can separate out the discipline of statistics. One of these ways is to classify statistical methods as either parametric or nonparametric.

Rudolph E. () Robustness of Many-One Statistics. In: Rasch D., Tiku M.L. (eds) Robustness of Statistical Methods and Nonparametric Statistics. Theory and Decision Library (Series B: Mathematical and Statistical Methods), vol 1.

This book points the environmental and water resources scientist to robust and nonparametric statistics, and to exploratory data analysis. We believe that the characteristics of environmental (and perhaps most other 'real') data drive analysis methods towards use of robust and nonparametric methods.

Exercises are included at the end of chapters. Selected papers from the Conference on Robustness of Statistical Methods and Nonparametric Statistics held in Schwerin, May June 4,and organized by the Mathematical Society of the GDR and others.

Description: pages: illustrations. Based in ranks of the data, this book offers an alternative to the traditional least squares approach. Topics include one- and two-sample location models, linear models (including multiple regression and designed experiments), and multivariate models.

Rank tests and estimates for all models are developed, including bounded influence and high breakdown methods. 3DGBOKPWBTMA Kindle» Robustness of Statistical Methods and Nonparametric Statistics Robustness of Statistical Methods and Nonparametric Statistics Filesize: MB Reviews This type of book is every thing and made me seeking forward and more.

It is amongst the most awesome publication we have go through. Presenting an extensive set of tools and methods for data analysis, Robust Nonparametric Statistical Methods, Second Edition covers univariate tests and estimates with extensions to linear models, multivariate models, times series models, experimental designs, and mixed models.

It follows the approach of the first edition by developing rank-based m. nonparametric methods in statistics Download nonparametric methods in statistics or read online books in PDF, EPUB, Tuebl, and Mobi Format.

Click Download or Read Online button to get nonparametric methods in statistics book now. This site is like a library, Use search box in the widget to get ebook that you want. The second edition of Robust Statistical Methods with R provides a systematic treatment of robust procedures with an emphasis on new developments and on the computational aspects.

There are many numerical examples and notes on the R environment, and the updated chapter on the multivariate model contains additional material on visualization of multivariate data in R. A new chapter on robust.Statistical significance Confidence intervals Power and robustness Degrees of freedom Non-parametric analysis 4 Descriptive statistics Counts and specific values Measures of central tendency Measures of spread Measures of distribution shape Statistical indices Hettmansperger and McKean examine a wealth of interesting problems in connection with applying nonparametric robust methods.

this is a well-written and nicely presented book that is likely to appeal to a reader with a good mathematical background and an interest in robust and nonparametric statistical : $