Handbook of Data Visualization

ISBN-13: 9783540330363 / Angielski / Twarda / 2007 / 936 str.

Chun-Houh Chen; Wolfgang Hdrdle; Antony Unwin

Opis

Antony Unwin, Chun-houh Chen, Wolfgang K. Hardle 1. 1 Computational Statistics and Data Visualization . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Data Visualization and Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Presentation and Exploratory Graphics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Graphics and Computing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 1. 2 The Chapters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Summary and Overview; Part II. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Summary and Overview; Part III. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Summary and Overview; Part IV . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 The Authors. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 1. 3 Outlook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 4 Antony Unwin, Chun-houh Chen, Wolfgang K. Hardle Computational Statistics 1. 1 and Data Visualization Tis book is the third volume of the Handbook of Computational Statistics and c- ers the ?eld of data visualization. In line with the companion volumes, it contains a collection of chapters by experts in the ?eld to present readers with an up-to-date and comprehensive overview of the state of the art. Data visualization is an active area of application and research, and this is a good time to gather together a summary of current knowledge. Graphic displays are ofen very e?ective at communicating information. Tey are also very ofen not e?ective at communicating information. Two important reasons for this state of a?airs are that graphics can be produced with a few clicks of the mouse without any thought and the design of graphics is not taken seriously in many scienti?c textbooks."

Recenzje

From the reviews:

"This handbook shows hundreds of ways to visualize data by using modern, high-quality statistical graphics. ... It is most enjoyable to see such a large number of specialists sharing their insights of these methods within one volume. This book really feeds the imagination of the reader. High-dimensionally recommended!" (Kimmo Vehkalahti, International Statistical Review, Vol. 76 (3), 2008)

Spis treści

Data Visualization: Introduction. Principles: A Brief History of Data Visualization.- Good Graphics?- Static Graphics.- Data Visualization Through Their Graph Representations.- Graph-Theoretic Graphics.- High Dimensional Data Visualization.- Multivariate Data Glyphs: Principles and Practice.- Linked Views for Visual Exploration.- Linked Data Views.- Visualizing Trees and Forests. Methodologies: Interactive Linked Micromap Plots for the Display of Geographically Referenced Statistical Data.-Grand Tours, Projection Pursuit Guided Tours and Manual Controls.- Multidimensional Scaling - A Review.- Huge Multidimensional Data Visualization: Back to the Virtue of Principal Coordinates and Dendrograms in the New Computer Age.- Multivariate Density Estimation for Visualization.- Structured Sets of Graphs.- Regression by Parts: Fitting Visually Interpretable Models with GUIDE.- Structural Adaptive Smoothing by Propagation-Separation-Methods.- Smoothing Techniques for Visualization.- Data Visualization via Kernel Machines.- Visualization of Cluster Analysis and Finite Mixture Models.- Visualizing Contingency Tables.- Mosaicplots and Their Variations.- Parallel Coordinates: Visualization and Classification of High Dimensional Datasets.- Matrix Visualization.- Visualization in Bayesian Analysis.- Java Tools and Environment for Statistical Data Visualization.- Web-Based Statistical Graphics Using XML Technologies. Selected Applications: Data Visualization for Genetic Networks Reconstruction.- Visualizing Genomic Data.- Reconstruction, Visualization, and Analysis of Medical Images.- Exploratory Graphics of a Financial Dataset.- Graphical Data Representation in Bankruptcy Analysis.- Visualizing Functional Data with an Application to eBay's Online Auctions.- Visualization Tools for Insurance Risk Processes.

O autorze

Wolfgang Härdle is a professor of statistics at the Humboldt-Universität zu Berlin and director of C.A.S.E. the Centre for Applied Statistics and Economics. He teaches quantitative finance and semiparametric statistical methods. His research focuses on dynamic factor models, multivariate statistics in finance and computational statistics. He is an elected ISI member and advisor to the Guanghua School of Management, Peking University and to National Central University, Taiwan.