| Description |
1 online resource |
| Series |
Monographs on statistics and applied probability ; 64 |
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Monographs on statistics and applied probability (Series) ; 64.
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| Contents |
Cover; MONOGRAPHS ONSTATISTICS AND APPLIED PROBABILITY; Title; Copyright; Contents; Preface; Chapter 1 Introduction; 1.1 Rank data; Chapter 2 Looking at Data; 2.1 Introduction: Permutation polytopes; 2.2 Projections of polytopes; 2.3 Marginals; 2.4 Pairs; 2.5 Center, spread, and distance; 2.5.1 Some useful distances; 2.5.2 Estimating the center; 2.5.3 Estimating spread, location known; 2.5.4 Estimating spread, location unknown; 2.5.5 Clustering: £-centers; 2.6 Linear su bspaces; 2.6.1 Spectral decomposition; 2.6.2 Inversions; 2.7 Exercises; Chapter 3 Formal Tests of Uniformity |
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3.1 Introduction3.2 Summary statistics; 3.2.1 Projections; 3.2.2 Probabilities; 3.2.3 Marginals; 3.2.4 Means; 3.2.5 Pairs; 3.3 lnvariance and monotonicity of distances; 3.4 Distance from a fixed vector; 3.4.1 Means and variances; 3.4.2 Exact distributions; 3.4.3 Asymptotics as m-oo; 3.5 One-sample diversity and concordance; 3.6 Summary; 3.7 Exercises; Chapter 4 Comparing Populations of Judges; 4.1 Introduction; 4.2 The basic statistics: Multivariate analysis ofvariance tests; 4.3 Distances from a modal ranking; 4.4 Concordance and diversity; 4.5 Exercises; Chapter 5 Overview of Models |
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5.1 Introduction5.2 Probability models -- General; 5.3 Thurstonian =O rder statistic models; 5.4 Distance-based models; 5.5 Paired comparison models -- Babington Smith; 5.5.1 Bradley-Terry /Mallows; 5.5.2 Mallows' models; 5.6 Multistage models; 5.6.1 Plackett-Luce; 5.6.2 Free and ÂØ-component models; 5. 7 Sufficient statistic models; 5.8 Loglinear models; 5.9 ANOVA-like models; 5.10 Nested orthogonal contrast models; 5.10.1 The free model; 5.10.2 The ÂØ model; 5.10.3 Contingency table models; 5.11 Unfolding models; 5.12 Generalizing the models; 5.13 Some axiomatics; 5.13.1 Luce's choice axiom |
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5.13.2 Unidimensionality, unimodality, and consensus5.14 Likelihood methods and exponential families; 5.4.1 The likelihood function and Fisher information; 5.1,/.2 Maximum likelihood estimation; 5.14.3 Likelihood ratio tests; 5.14.4 Exponential families; 5.15 Exercises; Chapter 6 Distance-Based Models; 6.1 Introduction; 6.2 Fitting the models: Known mode; 6.2.1 Kendall; 6.2.2 Cayley; 6.2.3 Hamming; 6.3 Unknown mode -- Likelihood; 6.4 Unknown mode -- Bayesian; 6.5 Asymptotics as m -- + oo; 6.5.1 Kendall; 6.5.2 Cayley; 6.5.3 Hamming; 6.5.4 Maximum; 6.6 Assessing fit; 6.6.1 Kendall |
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6.6.2 Hamming and Cayley6.7 Exercises; Chapter 7 Babington Smith, Phi-Models, and Inversions; 7.1 Introduction; 7.2 Babington Smith; 7.3 Contrast 4J models; 7.4 Bradley-Terry/Mallows and Spearman's distance models; 7.4.1 Bradley-Terry /Mallows; 7.4.2 Submodels of Bradley-Terry /Mallows, including Spearman; 7.4.3 Between Babington Smith and Bradley-Terry /Mallows; 7.5 Basic results for orthogonal contrast 4J models; 7.6 Details for the orthogonal contrast 4J models; 7.6.1 Preliminaries; 7.6.2 Null distribution for Kendall; 7.6.3 Non-null distribution for Phi, Mallows, and Kendall |
| Bibliography |
Includes bibliographical references and index |
| Notes |
Vendor-supplied metadata |
| Subject |
Ranking and selection (Statistics)
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MATHEMATICS -- Applied.
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MATHEMATICS -- Probability & Statistics -- General.
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Ranking and selection (Statistics)
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| Form |
Electronic book
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| ISBN |
9781482252491 |
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148225249X |
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