40% off Popular Science books & eBooks—Save on general interest titles now!

Behaviormetrics: Quantitative Approaches to Human Behavior
cover

Estimation of Mutual Information

Authors: Suzuki, Joe

  • Provides a developed theory that that is unique and specific rather than standard and average, and describes several cases such as discrete and continuous in a unified manner
  • Contains the whole proofs but chooses the most simple and comprehensive ones
  • Includes R codes and R packages (BNSL) for understanding the theory
おすすめポイントをすべて見る

書籍の購入

イーブック  
  • ISBN 978-981-13-0734-8
  • ウォーターマーク付、 DRMフリー
  • ファイル形式:
  • ebooks can be used on all reading devices
ハードカバー 約 ¥11,439
価格の適用国: Japan (日本円価格は個人のお客様のみ有効) (小計)
  • 予定日: December 11, 2021
  • ISBN 978-981-13-0733-1
  • Free shipping for individuals worldwide
  • Institutional customers should get in touch with their account manager
  • Covid-19 shipping restrictions
この書籍について

This book presents the mutual information (MI) estimation methods recently proposed by the author and published in a number of major journals. It includes two types of applications: learning a forest structure from data for multivariate variables and identifying independent variables (independent component analysis). MI between a pair of random variables is mathematically defined in information theory. It measures how dependent the two variables are, takes nonnegative values, and is zero if, and only if, they are independent, and is often necessary to know the value of MI between two variables in machine learning, statistical data analysis, and various sciences, including physics, psychology, and economics. However, the real value of MI is not available and it can only be estimated from data. The essential difference between this and other estimations is that consistency and independence testing are proved for the estimations proposed by the author, where the authors state that an estimation satisfies consistency and independence testing when the estimation corresponds to the true value and when the MI estimation value is zero with probability one as the sample size grows, respectively. Thus far, no MI estimations satisfy both these properties at once.

著者について

Joe Suzuki, Osaka University

書籍の購入

イーブック  
  • ISBN 978-981-13-0734-8
  • ウォーターマーク付、 DRMフリー
  • ファイル形式:
  • ebooks can be used on all reading devices
ハードカバー 約 ¥11,439
価格の適用国: Japan (日本円価格は個人のお客様のみ有効) (小計)
  • 予定日: December 11, 2021
  • ISBN 978-981-13-0733-1
  • Free shipping for individuals worldwide
  • Institutional customers should get in touch with their account manager
  • Covid-19 shipping restrictions

この書籍のサービス情報

あなたへのおすすめ

Loading...

書誌情報

Bibliographic Information
Book Title
Estimation of Mutual Information
Authors
Series Title
Behaviormetrics: Quantitative Approaches to Human Behavior
Series Volume
2
Copyright
2021
Publisher
Springer Singapore
Copyright Holder
Springer Nature Singapore Pte Ltd.
イーブック ISBN
978-981-13-0734-8
ハードカバー ISBN
978-981-13-0733-1
Series ISSN
2524-4027
Edition Number
1
Number of Pages
X, 120
Number of Illustrations
40 b/w illustrations, 20 illustrations in colour
Topics