Statistical Mining and Data Visualization in Atmospheric Sciences

✍ Scribed by Timothy J. Brown, Paul W. Mielke Jr. (auth.), Timothy J. Brown, Paul W. Mielke Jr. (eds.)

Publisher: Springer US
Year: 2000
Tongue: English
Leaves: 76
Edition: 1
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

Statistical Mining and Data Visualization in Atmospheric Sciences brings together in one place important contributions and up-to-date research results in this fast moving area.
Statistical Mining and Data Visualization in Atmospheric Sciences serves as an excellent reference, providing insight into some of the most challenging research issues in the field.

✦ Table of Contents

Front Matter....Pages 1-4
Guest Editorial: Statistical Mining and Data Visualization in Atmospheric Sciences....Pages 5-6
Euclidean Distance Based Permutation Methods in Atmospheric Science....Pages 7-27
Bootstrapping to Assess and Improve Atmospheric Prediction Models....Pages 29-41
Using Linked Micromap Plots to Characterize Omernik Ecoregions....Pages 43-67
Visual Data Mining in Atmospheric Science Data....Pages 69-80

✦ Subjects

Data Structures, Cryptology and Information Theory; Geographical Information Systems/Cartography; Artificial Intelligence (incl. Robotics); Statistics, general

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