Buch, Englisch, 936 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 1410 g
Buch, Englisch, 936 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 1410 g
Reihe: Springer Handbooks of Computational Statistics
ISBN: 978-3-662-50074-3
Verlag: Springer
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen
- Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
- Mathematik | Informatik EDV | Informatik Angewandte Informatik Bioinformatik
- Mathematik | Informatik EDV | Informatik Informatik Bildsignalverarbeitung
- Naturwissenschaften Biowissenschaften Angewandte Biologie Bioinformatik
Weitere Infos & Material
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.