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Grade Models and Methods for Data Analysis

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Cover of 'Grade Models and Methods for Data Analysis'

Table of Contents

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    Book Overview
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    Chapter 1 Grade Data Analysis — A First Look
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    Chapter 2 The Grade Approach
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    Chapter 3 Univariate Lilliputian Model I
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    Chapter 4 Univariate Lilliputian Model II
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    Chapter 5 Asymmetry and the inverse concentration set
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    Chapter 6 Discretization and regularity
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    Chapter 7 Preliminary concepts of bivariate dependence
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    Chapter 8 Dependence Lilliputian Model
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    Chapter 9 Grade Correspondence Analysis and outlier detection
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    Chapter 10 Cluster analysis based on GCA
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    Chapter 11 Regularity and the number of clusters
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    Chapter 12 Grade approach to the analysis of finite data matrices
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    Chapter 13 Inequality measures for multivariate distributions
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    Chapter 14 Case studies with multivariate data
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    Chapter 15 The GradeStat program
Attention for Chapter 6: Discretization and regularity
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