Statistical Mining and Data Visualization in Atmospheric Sciences

  • Timothy J. Brown
  • Paul W. MielkeJr.

Table of contents

  1. Front Matter
    Pages 1-4
  2. Paul W. Mielke Jr., Kenneth J. Berry
    Pages 7-27
  3. Daniel B. Carr, Anthony R. Olsen, Suzanne M. Pierson, Jean-Yves P. Courbois
    Pages 43-67
  4. Márcia Macêdo, Dianne Cook, Timothy J. Brown
    Pages 69-80

About this book

Introduction

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.

Keywords

Bootstrapping Excel data mining mutation visualization

Editors and affiliations

  • Timothy J. Brown
    • 1
  • Paul W. MielkeJr.
    • 2
  1. 1.Desert Research InstituteUSA
  2. 2.Colorado State UniversityUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4757-6581-6
  • Copyright Information Springer-Verlag US 2000
  • Publisher Name Springer, Boston, MA
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4419-4974-5
  • Online ISBN 978-1-4757-6581-6
  • About this book