发个论坛上没有的。很重要也很有意思的一本书。

With 569 Figures and 50 Tables

Table of Contents
I. Data Visualization
I.1 Introduction
Antony Unwin, Chun-houh Chen,Wolfgang K. Härdle . . . . . . . . . . . . . . . . . . . . . . . . . . 3
II. Principles
II.1 A Brief History of Data Visualization
Michael Friendly . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
II.2 Good Graphics?
Antony Unwin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
II.3 Static Graphics
Paul Murrell . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .79
II.4 Data Visualization Through Their Graph Representations
George Michailidis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103
II.5 Graph-theoretic Graphics
LelandWilkinson . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121
II.6 High-dimensional Data Visualization
Martinheus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .151
II.7Multivariate Data Glyphs: Principles and Practice
Matthew O.Ward . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179
II.8 Linked Views for Visual Exploration
AdalbertWilhelm. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 199
II.9 Linked Data Views
GrahamWills . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 217
II.10 Visualizing Trees and Forests
Simon Urbanek . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 243
VI Table of Contents
III. Methodologies
III.1 Interactive Linked Micromap Plots for the Display
of Geographically Referenced Statistical Data
Jürgen Symanzik, Daniel B. Carr . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 267
III.2 Grand Tours, Projection Pursuit Guided Tours, and Manual Controls
Dianne Cook, Andreas Buja, Eun-Kyung Lee, HadleyWickham. . . . . . . . . . . . . . . . 295
III.3Multidimensional Scaling
Michael A.A. Cox, Trevor F. Cox . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 315
III.4 Huge Multidimensional Data Visualization: Back to the Virtue
of Principal Coordinates and Dendrograms in the New Computer Age
Francesco Palumbo, Domenico Vistocco, AlainMorineau. . . . . . . . . . . . . . . . . . . . . .349
III.5Multivariate Visualization by Density Estimation
Michael C. Minnotte, Stephan R. Sain, DavidW. Scott . . . . . . . . . . . . . . . . . . . . . . . . 389
III.6 Structured Sets of Graphs
Richard M. Heiberger, Burt Holland . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 415
III.7 Regression by Parts:
Fitting Visually InterpretableModels with GUIDE
Wei-Yin Loh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 447
III.8 Structural Adaptive Smoothing
by Propagation–Separation Methods
Jörg Polzehl, Vladimir Spokoiny . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 471
III.9 Smoothing Techniques for Visualisation
AdrianW. Bowman . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 493
III.10 Data Visualization via Kernel Machines
Yuan-chin Ivan Chang, Yuh-Jye Lee, Hsing-Kuo Pao, Mei-Hsien Lee,
Su-Yun Huang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .539
III.11 Visualizing Cluster Analysis and Finite Mixture Models
Friedrich Leisch. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .561
III.12 Visualizing Contingency Tables
DavidMeyer, Achim Zeileis, Kurt Hornik . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 589
III.13 Mosaic Plots and Their Variants
Heike Hofmann. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .617
III.14 Parallel Coordinates: Visualization, Exploration
and Classiication of High-Dimensional Data
Alfred Inselberg . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 643
III.15 Matrix Visualization
Han-MingWu, ShengLi Tzeng, Chun-Houh Chen . . . . . . . . . . . . . . . . . . . . . . . . . . . . 681
III.16 Visualization in Bayesian Data Analysis
Jouni Kerman, Andrew Gelman, Tian Zheng, Yuejing Ding . . . . . . . . . . . . . . . . . . . . 709
III.17 Programming Statistical Data Visualization in the Java Language
Junji Nakano, Yoshikazu Yamamoto, Keisuke Honda . . . . . . . . . . . . . . . . . . . . . . . . . 725
III.18Web-Based Statistical Graphics using XML Technologies
Yoshiro Yamamoto, Masaya Iizuka, Tomokazu Fujino . . . . . . . . . . . . . . . . . . . . . . . . 757
Table of Contents VII
IV. Selected Applications
IV.1 Visualization for Genetic Network Reconstruction
Grace S. Shieh, Chin-Yuan Guo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 793
IV.2 Reconstruction, Visualization and Analysis of Medical Images
Henry Horng-Shing Lu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 813
IV.3 Exploratory Graphics of a Financial Dataset
AntonyUnwin,Martinheus, Wolfgang K. Härdle . . . . . . . . . . . . . . . . . . . . . . . . . . . 831
IV.4 Graphical Data Representation in Bankruptcy Analysis
Wolfgang K. Härdle, Rouslan A. Moro, Dorothea Schäfer . . . . . . . . . . . . . . . . . . . . . . 853
IV.5 Visualizing Functional Data with an Application
to eBay’s Online Auctions
Wolfgang Jank, Galit Shmueli, Catherine Plaisant, Ben Shneiderman . . . . . . . . . . . 873
IV.6 Visualization Tools for Insurance Risk Processes
Krzysztof Burnecki, RafałWeron . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 899