Handbook of Data Visualization

by Chen, Chun-houh; Hardle, Wolfgang; Unwin, Antony

• ISBN13: 9783540330363
• ISBN10: 3540330364
• Format: Hardcover
• Copyright: 2008-04-30
• Publisher: Springer Verlag

Summary

Visualizing the data is an essential part of any data analysis. Modern computing developments have led to big improvements in graphic capabilities and there are many new possibilities for data displays. This new volume in the series Springer Handbooks of Computational Statistics gives an overview of modern data visualization methods, both in theory and practice. There are definitive chapters on modern graphical tools such as mosaic plots, parallel coordinate plots and linked views. There are chapters dedicated to graphical methodology for particular areas of statistics, for example Bayesian analysis, genomic data and cluster analysis, as well as chapters on software for graphics. Specialists from all over the world have contributed papers on their areas of expertise.

Table of Contents

Data Visualization
Introduction	p. 3
Principles
A Brief History of Data Visualization	p. 15
Good Graphics?	p. 57
Static Graphics	p. 79
Data Visualization Through Their Graph Representations	p. 103
Graph-theoretic Graphics	p. 121
High-dimensional Data Visualization	p. 151
Multivariate Data Glyphs: Principles and Practice	p. 179
Linked Views for Visual Exploration	p. 199
Linked Data Views	p. 217
Visualizing Trees and Forests	p. 243
Methodologies
Interactive Linked Micromap Plots for the Display of Geographically Referenced Statistical Data	p. 267
Grand Tours, Projection Pursuit Guided Tours, and Manual Controls	p. 295
Multidimensional Scaling	p. 315
Huge Multidimensional Data Visualization: Back to the Virtue of Principal Coordinates and Dendrograms in the New Computer Age	p. 349
Multivariate Visualization by Density Estimation	p. 389
Structured Sets of Graphs	p. 415
Regression by Parts: Fitting Visually Interpretable Models with GUIDE	p. 447
Structural Adaptive Smoothing by Propagation-Separation Methods	p. 471
Smoothing Techniques for Visualisation	p. 493
Data Visualization via Kernel Machines	p. 539
Visualizing Cluster Analysis and Finite Mixture Models	p. 561
Visualizing Contingency Tables	p. 589
Mosaic Plots and Their Variants	p. 617
Parallel Coordinates: Visualization, Exploration and Classification of High-Dimensional Data	p. 643
Matrix Visualization	p. 681
Visualization in Bayesian Data Analysis	p. 709
Programming Statistical Data Visualization in the Java Language	p. 725
Web-Based Statistical Graphics using XML Technologies	p. 757
Selected Applications
Visualization for Genetic Network Reconstruction	p. 793
Reconstruction, Visualization and Analysis of Medical Images	p. 813
Exploratory Graphics of a Financial Dataset	p. 831
Graphical Data Representation in Bankruptcy Analysis	p. 853
Visualizing Functional Data with an Application to eBay's Online Auctions	p. 873
Visualization Tools for Insurance Risk Processes	p. 899
Subject Index	p. 921
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