LEADER 05469nam 2200673Ia 450 001 9910139929603321 005 20170810193228.0 010 $a1-282-38215-2 010 $a9786612382154 010 $a0-470-82444-1 010 $a0-470-82443-3 035 $a(CKB)1000000000799889 035 $a(EBL)479828 035 $a(OCoLC)521034718 035 $a(SSID)ssj0000365947 035 $a(PQKBManifestationID)11296468 035 $a(PQKBTitleCode)TC0000365947 035 $a(PQKBWorkID)10413875 035 $a(PQKB)11755440 035 $a(MiAaPQ)EBC479828 035 $a(EXLCZ)991000000000799889 100 $a20090121d2009 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aSmooth tests of goodness of fit$b[electronic resource] /$fJ.C.W. Rayner, O. Thas, D.J. Best 205 $a2nd ed. 210 $aHoboken, NJ $cWiley$dc2009 215 $a1 online resource (300 p.) 225 0 $aWiley series in probability and statistics Smooth tests of goodness of fit using R 300 $aDescription based upon print version of record. 311 $a0-470-82442-5 320 $aIncludes bibliographical references and index. 327 $aSMOOTH TESTS OF GOODNESS OF FIT USING R; Contents; Preface; 1 Introduction; 1.1 The Problem Defined; 1.2 A Brief History of Smooth Tests; 1.3 Monograph Outline; 1.4 Examples; 2 Pearson's X2 Test; 2.1 Introduction; 2.2 Foundations; 2.3 The Pearson X2 Test - an Update; 2.3.1 Notation, Definition of the Test, and Class Construction; 2.3.2 Power Related Properties; 2.3.3 The Sample Space Partition Approach; 2.4 X2 Tests of Composite Hypotheses; 2.5 Examples; 3 Asymptotically Optimal Tests; 3.1 Introduction; 3.2 The Likelihood Ratio, Wald, and Score Tests for a Simple Null Hypothesis 327 $a3.3 The Likelihood Ratio, Wald and Score Tests for Composite Null Hypotheses3.4 Generalized Score Tests; 4 Neyman Smooth Tests for Simple Null Hypotheses; 4.1 Neyman's ?2 test; 4.2 Neyman Smooth Tests for Uncategorized Simple Null Hypotheses; 4.3 The Choice of Order; 4.4 Examples; 4.5 EDF Tests; 5 Categorized Simple Null Hypotheses; 5.1 Smooth Tests for Completely Specified Multinomials; 5.2 X2 Effective Order; 5.3 Components of X2P; 5.3.1 Construction of the Components; 5.3.2 Power Study; 5.3.3 Diagnostic Tests; 5.3.4 Cressie and Read Tests; 5.4 Examples; 5.5 Class Construction 327 $a5.5.1 The Alternatives5.5.2 Results of the Simulation Study; 5.5.3 Discussion; 5.6 A More Comprehensive Class of Tests; 5.7 Overlapping Cells Tests; 6 Neyman Smooth Tests for Uncategorized Composite Null Hypotheses; 6.1 Neyman Smooth Tests for Uncategorized Composite Null Hypotheses; 6.2 Smooth Tests for the Univariate Normal Distribution; 6.2.1 The Construction of the Smooth Test; 6.2.2 Simulation Study; 6.2.3 Examples; 6.2.4 Relationship with a Test of Thomas and Pierce; 6.3 Smooth Tests for the Exponential Distribution; 6.4 Smooth Tests for Multivariate Normal Distribution 327 $a6.5 Smooth Tests for the Bivariate Poisson Distribution6.5.1 Definitions; 6.5.2 Score Tests for the Bivariate Poisson Model; 6.5.3 A Smooth Covariance Test; 6.5.4 Variance Tests; 6.5.5 A Competitor for the Index of Dispersion Test; 6.5.6 Revised Index of Dispersion and Crockett Tests; 6.6 Components of the Rao-Robson X2 Statistic; 7 Neyman Smooth Tests for Categorized Composite Null Hypotheses; 7.1 Neyman Smooth Tests for Composite Multinomials; 7.2 Components of the Pearson-Fisher Statistic; 7.3 Composite Overlapping Cells and Cell Focusing X2 Tests 327 $a7.4 A Comparison between the Pearson-Fisher and Rao-Robson X2 Tests8 Neyman Smooth Tests for Uncategorized Composite Null Hypotheses: Discrete Distributions; 8.1 Neyman Smooth Tests for Discrete Uncategorized Composite Null Hypotheses; 8.2 Smooth and EDF Tests for the Univariate Poisson Distribution; 8.2.1 Definitions; 8.2.2 Size and Power Study; 8.2.3 Examples; 8.3 Smooth and EDF Tests for the Binomial Distribution; 8.3.1 Definitions; 8.3.2 Size and Power Study; 8.3.3 Examples; 8.4 Smooth Tests for the Geometric Distribution; 8.4.1 Definitions; 8.4.2 Size and Power Study; 8.4.3 Examples 327 $a9 Construction of Generalized Smooth Tests: Theoretical Contributions 330 $aIn 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 n 606 $aGoodness-of-fit tests 606 $aStatistical hypothesis testing 608 $aElectronic books. 615 0$aGoodness-of-fit tests. 615 0$aStatistical hypothesis testing. 676 $a519.5/6 676 $a519.56 700 $aRayner$b J. C. W$0248333 701 $aBest$b D. J$0248334 701 $aThas$b O$g(Olivier)$0955818 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910139929603321 996 $aSmooth tests of goodness of fit$92163481 997 $aUNINA