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  • Format: PDF


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…mehr

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Produktbeschreibung
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. TOC:Data Visualization.- Principles.- Methodologies.- Selected Applications.

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  • Produktdetails
  • Verlag: Springer-Verlag GmbH
  • Erscheinungstermin: 18.12.2007
  • Englisch
  • ISBN-13: 9783540330370
  • Artikelnr.: 37369664
Autorenporträt
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.
Inhaltsangabe
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.
Rezensionen
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)