Description
Book SynopsisThe first book to present a unified account of symbolic data analysis methods in a consistent statistical framework, Symbolic Data Analysis features a substantial number of examples from a range of application areas, including health, the social sciences, economics, and computer science.
Trade Review“Primarily aimed at statisticians and Data analysts, SDA is also ideal for scientists…” (
Zentralblatt MATH, 2007)
Table of Contents1. Introduction.
References.
2. Symbolic Data.
2.1 Symbolic and Classical Data.
2.2 Categories, Concepts and Symbolic Objects.
2.3 Comparison of Symbolic and Classical Analysis.
3. Basic Descriptive Statistics: One Variate.
3.1 Some Preliminaries.
3.2 Multi-valued Variables.
3.3 Interval-valued Variables.
3.4 Multi-valued Modal variables.
3.5 Interval-valued Modal Variables.
4. Descriptive Statistics: Two or More Variates.
4.1 Multi-valued Variables.
4.2 Interval-valued Variables.
4.3 Modal Multi-valued Variables.
4.4 Modal Interval-valued Variables.
4.5 Baseball Interval-valued Dataset.
4.6 Measures of Dependence.
5. Principal Component Analysis.
5.1 Vertices Method.
5.2 Centers Method.
5.3 Comparison of the Methods.
6. Regression Analysis.
6.1 Classical Multiple Regression Model.
6.2 Multi-valued Variables.
6.3 Interval-valued Variables.
6.4 Histogram-valued Variables.
6.5 Taxonomy Variables.
6.6 Hierarchical Variables.
7. Cluster Analysis.
7.1 Dissimilarity and Distance Measures.
7.2 Clustering Structures.
7.3 Partitions.
7.4 Hierarchy-Divisive Clustering.
7.5 Hierarchy-Pyramid Clusters.
Data Index.
Author Index.
Subject Index.
