Handbook of Data Visualization

ISBN-13: 9783662500743 / Angielski / Miękka / 2016 / 936 str.

Chun-Houh Chen;Wolfgang Hdrdle;Antony Unwin (University of Augsburg)

Opis

This book gives an overview of modern data visualization methods, both in theory and practice. It details modern graphical tools, graphical methodology for particular areas of statistics, as well software for graphics.

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.