Goodness-of-fit Tests for Bivariate Normality PDF Download

Author: Marcus Tracktir Simon
Publisher:
ISBN:
Category : Goodness-of-fit tests
Languages : en
Pages : 242

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Book Description

Author: Ralph B. D'Agostino
Publisher: CRC Press
ISBN: 9780824774875
Category : Mathematics
Languages : en
Pages : 590

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Book Description
Conveniently grouping methods by techniques, such as chi-squared and empirical distributionfunction, and also collecting methods of testing for specific famous distributions, this useful reference is the first comprehensive review of the extensive literature on the subject. It surveysthe leading methods of testing fit . .. provides tables to make the tests available . .. assessesthe comparative merits of different test procedures . .. and supplies numerical examples to aidin understanding these techniques.Goodness-of-Fit Techniques shows how to apply the techniques . .. emphasizes testing for thethree major distributions, normal, exponential, and uniform . .. discusses the handling of censoreddata .. . and contains over 650 bibliographic citations that cover the field.Illustrated with tables and drawings, this volume is an ideal reference for mathematical andapplied statisticians, and biostatisticians; professionals in applied science fields, including psychologists, biometricians, physicians, and quality control and reliability engineers; advancedundergraduate- and graduate-level courses on goodness-of-fit techniques; and professional seminarsand symposia on applied statistics, quality control, and reliability.

Author: Henry C. Thode
Publisher: CRC Press
ISBN: 9780203910894
Category : Mathematics
Languages : en
Pages : 506

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Book Description
Describes the selection, design, theory, and application of tests for normality. Covers robust estimation, test power, and univariate and multivariate normality. Contains tests ofr multivariate normality and coordinate-dependent and invariant approaches.

Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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Book Description
The paper is an investigation of a goodness of fit test for bivariate normal distributions. The test procedure is based on random linear functions of bivariate normal random variables. The test makes use of the maximum Kolmogorov D(M) statistic over the linear functions which are computed. An estimate of the distribution of M is obtained by computer simulation. No attempt is made to determine the power of the test. (Author).

Author: J. C. W. Rayner
Publisher: Oxford University Press
ISBN: 0195363604
Category : Mathematics
Languages : en
Pages : 177

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Book Description
Goodness of fit describes the validity of models involving statistical distributions of data, and smooth tests are a subset of these tests that are easy to apply and can be used in any situation in which there are relatively large sample sizes. Both concepts have become increasingly important with the advent of high-speed computers and the implementation of more complex models in the areas of probability and statistics. Written to be accessible to undergraduates with a knowledge of statistics and calculus, this is an introductory reference work that should appeal to all professionals involved in statistical modeling.

Author: Nabil Ali Ahmed
Publisher:
ISBN:
Category : Entropy (Information theory)
Languages : en
Pages : 316

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Book Description

Author: J. C. W. Rayner
Publisher: John Wiley & Sons
ISBN: 0470824433
Category : Mathematics
Languages : en
Pages : 300

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Book Description
In this fully revised and expanded edition of Smooth Tests of Goodness of Fit, the latest powerful techniques for assessing statistical and probabilistic models using this proven class of procedures are presented in a practical and easily accessible manner. Emphasis is placed on modern developments such as data-driven tests, diagnostic properties, and model selection techniques. Applicable to most statistical distributions, the methodology described in this book is optimal for deriving tests of fit for new distributions and complex probabilistic models, and is a standard against which new procedures should be compared. New features of the second edition include: Expansion of the methodology to cover virtually any statistical distribution, including exponential families Discussion and application of data-driven smooth tests Techniques for the selection of the best model for the data, with a guide to acceptable alternatives Numerous new, revised, and expanded examples, generated using R code Smooth Tests of Goodness of Fit is an invaluable resource for all methodological researchers as well as graduate students undertaking goodness-of-fit, statistical, and probabilistic model assessment courses. Practitioners wishing to make an informed choice of goodness-of-fit test will also find this book an indispensible guide. Reviews of the first edition: "This book gives a very readable account of the smooth tests of goodness of fit. The book can be read by scientists having only an introductory knowledge of statistics. It contains a fairly extensive list of references; research will find it helpful for the further development of smooth tests." --T.K. Chandra, Zentralblatt für Mathematik und ihre Grenzgebiete, Band 73, 1/92' "An excellent job of showing how smooth tests (a class of goodness of fit tests) are generally and easily applicable in assessing the validity of models involving statistical distributions....Highly recommended for undergraduate and graduate libraries." --Choice "The book can be read by scientists having only an introductory knowledge of statistics. It contains a fairly extensive list of references; researchers will find it helpful for the further development of smooth tests."--Mathematical Reviews "Very rich in examples . . . Should find its way to the desks of many statisticians." --Technometrics

Author: N. Balakrishnan
Publisher: Academic Press
ISBN: 0123977835
Category : Mathematics
Languages : en
Pages : 256

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Book Description
Chi-Squared Goodness of Fit Tests with Applications provides a thorough and complete context for the theoretical basis and implementation of Pearson’s monumental contribution and its wide applicability for chi-squared goodness of fit tests. The book is ideal for researchers and scientists conducting statistical analysis in processing of experimental data as well as to students and practitioners with a good mathematical background who use statistical methods. The historical context, especially Chapter 7, provides great insight into importance of this subject with an authoritative author team. This reference includes the most recent application developments in using these methods and models. Systematic presentation with interesting historical context and coverage of the fundamentals of the subject Presents modern model validity methods, graphical techniques, and computer-intensive methods Recent research and a variety of open problems Interesting real-life examples for practitioners

Author: C. Huber-Carol
Publisher: Springer Science & Business Media
ISBN: 1461201039
Category : Mathematics
Languages : en
Pages : 512

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Book Description
The 37 expository articles in this volume provide broad coverage of important topics relating to the theory, methods, and applications of goodness-of-fit tests and model validity. The book is divided into eight parts, each of which presents topics written by expert researchers in their areas. Key features include: * state-of-the-art exposition of modern model validity methods, graphical techniques, and computer-intensive methods * systematic presentation with sufficient history and coverage of the fundamentals of the subject * exposure to recent research and a variety of open problems * many interesting real life examples for practitioners * extensive bibliography, with special emphasis on recent literature * subject index This comprehensive reference work will serve the statistical and applied mathematics communities as well as practitioners in the field.

Author: José Kreimerman
Publisher:
ISBN:
Category : Distribution (Probability theory)
Languages : en
Pages : 186

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Book Description
An important area of Statistical Inference relates to the problem of assessing the conformity or goodness of fit of some observations to a null hypothesis. This hypothesis may be that the observations came from a distribution which belongs to a given family or may be a completely specified distribution. A statistical procedure which solves such a problem is called a test of goodness of fit. This thesis is concerned with the problem of testing the goodness of fit of a sample drawn from a continuous bivariate distribution, where the null hypothesis is that the true distribution is a completely specified one. A test is developed, where the test criterion is based in some functions of a subset of order statistics, functions which depend on the distribution under the null hypothesis.