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Nonparametric Methods in Change Point Problems

Nonparametric Methods in Change Point Problems
Author: E. Brodsky
Publisher: Springer Science & Business Media
Total Pages: 221
Release: 2013-03-14
Genre: Mathematics
ISBN: 9401581630

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The explosive development of information science and technology puts in new problems involving statistical data analysis. These problems result from higher re quirements concerning the reliability of statistical decisions, the accuracy of math ematical models and the quality of control in complex systems. A new aspect of statistical analysis has emerged, closely connected with one of the basic questions of cynergetics: how to "compress" large volumes of experimental data in order to extract the most valuable information from data observed. De tection of large "homogeneous" segments of data enables one to identify "hidden" regularities in an object's behavior, to create mathematical models for each seg ment of homogeneity, to choose an appropriate control, etc. Statistical methods dealing with the detection of changes in the characteristics of random processes can be of great use in all these problems. These methods have accompanied the rapid growth in data beginning from the middle of our century. According to a tradition of more than thirty years, we call this sphere of statistical analysis the "theory of change-point detection. " During the last fifteen years, we have witnessed many exciting developments in the theory of change-point detection. New promising directions of research have emerged, and traditional trends have flourished anew. Despite this, most of the results are widely scattered in the literature and few monographs exist. A real need has arisen for up-to-date books which present an account of important current research trends, one of which is the theory of non parametric change--point detection.


A Distribution-Free Theory of Nonparametric Regression

A Distribution-Free Theory of Nonparametric Regression
Author: László Györfi
Publisher: Springer Science & Business Media
Total Pages: 662
Release: 2006-04-18
Genre: Mathematics
ISBN: 0387224424

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This book provides a systematic in-depth analysis of nonparametric regression with random design. It covers almost all known estimates. The emphasis is on distribution-free properties of the estimates.


Distribution-Free Statistical Methods

Distribution-Free Statistical Methods
Author: J. S. Maritz
Publisher: Springer
Total Pages: 282
Release: 1981
Genre: Mathematics
ISBN:

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Basic concepts in distribution-free methods; One-sample location problems; Miscellaneous one-sample problems; Two-sample problems; Straight-line regression; Multiple regression and general linear models; Bivariate problems; Appendix; Bibliography.


Applied Nonparametric Statistical Methods

Applied Nonparametric Statistical Methods
Author: Peter Sprent
Publisher: CRC Press
Total Pages: 536
Release: 2016-04-19
Genre: Mathematics
ISBN: 1439894019

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While preserving the clear, accessible style of previous editions, Applied Nonparametric Statistical Methods, Fourth Edition reflects the latest developments in computer-intensive methods that deal with intractable analytical problems and unwieldy data sets. Reorganized and with additional material, this edition begins with a brief summary of some


Distribution-free Statistics

Distribution-free Statistics
Author: Joachim Krauth
Publisher: Elsevier Publishing Company
Total Pages: 404
Release: 1988
Genre: Mathematics
ISBN:

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This is a practical non-parametric handbook of statistical tests for use in general research, but particularly useful in the fields of Behavioural and Neural Sciences. Topics covered include: a full explanation of statistical terms, correct test choice and applications, small and large sample procedures, interpretation of test results, dependence testing and independent and dependent testing of two, three or more samples. Many of these tests are based on extensive modern statistical research, so are more relevant and accurate than the earlier book on the subject (Siegel 1956). Results obtained from traditional and modern methodologies have been investigated and included for comparison of significance and variance by the reader.


Nonparametric Statistics

Nonparametric Statistics
Author: Gregory W. Corder
Publisher: John Wiley & Sons
Total Pages: 288
Release: 2014-04-14
Genre: Mathematics
ISBN: 1118840429

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“...a very useful resource for courses in nonparametric statistics in which the emphasis is on applications rather than on theory. It also deserves a place in libraries of all institutions where introductory statistics courses are taught." –CHOICE This Second Edition presents a practical and understandable approach that enhances and expands the statistical toolset for readers. This book includes: New coverage of the sign test and the Kolmogorov-Smirnov two-sample test in an effort to offer a logical and natural progression to statistical power SPSS® (Version 21) software and updated screen captures to demonstrate how to perform and recognize the steps in the various procedures Data sets and odd-numbered solutions provided in an appendix, and tables of critical values Supplementary material to aid in reader comprehension, which includes: narrated videos and screen animations with step-by-step instructions on how to follow the tests using SPSS; online decision trees to help users determine the needed type of statistical test; and additional solutions not found within the book.


Nonparametric Statistical Methods

Nonparametric Statistical Methods
Author: Myles Hollander
Publisher: Wiley-Interscience
Total Pages: 900
Release: 1999-01-25
Genre: Mathematics
ISBN:

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An extensive array of examples drawn from actual experiments illustrates clearly how to use nonparametric approaches to handle one- or two-sample location and dispersion problems, dichotomous data, and one-way and two-way layout problems.


Applied Nonparametric Statistical Methods

Applied Nonparametric Statistical Methods
Author: Peter Sprent
Publisher: Springer Science & Business Media
Total Pages: 268
Release: 2012-12-06
Genre: Science
ISBN: 9400912234

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This book is a practical introduction to statistical techniques called nonpara metric methods. Using examples, we explain assumptions and demonstrate procedures; theory is kept to a minimum. We show how basic problems are tackled and try to clear up common misapprehensions so as to help both students of statistics meeting the methods for the first time and workers in other fields faced with data needing simple but informative analysis. An analogy between experimenters and car drivers describes our aim. Statistical analyses may be done by following a set of rules without understanding their logical basis, but this has dangers. It is like driving a car with no inkling ofhow the internal combustion engine, the gears, the ignition system, the brakes actually work. Understanding the rudiments helps one get better performance and makesdrivingsafer;appropriate gearchanges become a way to reduce engine stress, prolong engine life, improve fuel economy, minimize wear on brake linings. Knowing how to change the engine oil or replace worn sparking plugs is notessential for adriver, but it will reduce costs. Learning such basics will not make one a fully fledged mechanic, even less an automotive engineer; but it all contributes to more economical and safer driving, alertingone to the dangers ofbald tyres, aleakingexhaust, worn brake linings.