Smooth Tests of Goodness of Fit :Using R

Publication subTitle :Using R

Author: J. C. W. Rayner  

Publisher: John Wiley & Sons Inc‎

Publication year: 2009

E-ISBN: 9780470824436

P-ISBN(Hardback):  9780470824429

Subject: O212 Statistics

Language: ENG

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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

Chapter

Contents

pp.:  1 – 9

Preface

pp.:  9 – 15

1 Introduction

pp.:  15 – 19

2 Pearson’s X² Test

pp.:  19 – 35

3 Asymptotically Optimal Tests

pp.:  35 – 51

4 Neyman Smooth Tests for Simple Null Hypotheses

pp.:  51 – 71

5 Categorized Simple Null Hypotheses

pp.:  71 – 83

6 Neyman Smooth Tests for Uncategorized Composite Null Hypotheses

pp.:  83 – 113

7 Neyman Smooth Tests for Categorized Composite Null Hypotheses

pp.:  113 – 155

8 Neyman Smooth Tests for Uncategorized Composite Null Hypotheses: Discrete Distributions

pp.:  155 – 169

9 Construction of Generalized Smooth Tests: Theoretical Contributions

pp.:  169 – 197

10 Smooth Modelling

pp.:  197 – 217

11 Generalized Smooth Tests for Uncategorized Composite Null Hypotheses

pp.:  217 – 239

Appendix A: Orthonormal Polynomials and Recurrence Relations

pp.:  239 – 261

Appendix B: Parametric Bootstrap p-Values

pp.:  261 – 265

Appendix C: Some Details for Particular Distributions

pp.:  265 – 267

References

pp.:  267 – 277

Subject Index

pp.:  277 – 287

Author Index

pp.:  287 – 289

Example Index

pp.:  289 – 291

Series Pages

pp.:  291 – 293

LastPages

pp.:  293 – 300

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