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Handbook of Data Visualization de Chun-Houh Chen

Handbook of Data Visualization: Springer Handbooks of Computational Statistics

Editat de Chun-Houh Chen, Wolfgang Karl Härdle, Antony Unwin
en Limba Engleză Paperback – 23 aug 2016
Antony Unwin, Chun-houh Chen, Wolfgang K. Härdle 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. Härdle Computational Statistics 1. 1 and DataVisualization 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.
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Specificații

ISBN-13: 9783662500743
ISBN-10: 3662500744
Pagini: 952
Ilustrații: XIII, 936 p.
Dimensiuni: 155 x 235 x 51 mm
Greutate: 1.41 kg
Ediția:Softcover reprint of the original 1st ed. 2008
Editura: Springer
Colecția Springer Handbooks of Computational Statistics
Seria Springer Handbooks of Computational Statistics

Locul publicării:Berlin, Heidelberg, Germany

Cuprins

Data Visualization.- 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.- Huge Multidimensional Data Visualization: Back to the Virtue of Principal Coordinates and Dendrograms in the New Computer Age.- Multivariate Visualization by Density Estimation.- Structured Sets of Graphs.- Regression by Parts: Fitting Visually Interpretable Models with GUIDE.- Structural Adaptive Smoothing by Propagation–Separation Methods.- Smoothing Techniques for Visualisation.- Data Visualization via Kernel Machines.- Visualizing Cluster Analysis and Finite Mixture Models.- Visualizing Contingency Tables.- Mosaic Plots and Their Variants.- Parallel Coordinates: Visualization, Exploration and Classification of High-Dimensional Data.- Matrix Visualization.- Visualization in Bayesian Data Analysis.- Programming Statistical Data Visualization in the Java Language.- Web-Based Statistical Graphics using XML Technologies.- Selected Applications.- Visualization for Genetic Network Reconstruction.- 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.

Recenzii

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)

Caracteristici

Complete overview of data visualization Comprehensive coverage of the field, both in theory and practice Includes supplementary material: sn.pub/extras