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Introduction to Multivariate Analysis : Linear and Nonlinear Modeling.

Author: Sadanori Konishi
Publisher: Hoboken : CRC Press, 2014.
Series: Chapman & Hall/CRC Texts in Statistical Science.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Database:WorldCat
Summary:
""The presentation is always clear and several examples and figures facilitate an easy understanding of all the techniques. The book can be used as a textbook in advanced undergraduate courses in multivariate analysis, and can represent a valuable reference manual for biologists and engineers working with multivariate datasets.""--Fabio Rapallo, Zentralblatt MATH 1296.
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Konishi, Sadanori.
Introduction to Multivariate Analysis : Linear and Nonlinear Modeling.
Hoboken : CRC Press, ©2014
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Sadanori Konishi
ISBN: 9781466567290 1466567295
OCLC Number: 908078757
Description: 1 online resource (336 pages).
Contents: Front Cover; Contents; List of Figures; List of Tables; Preface; 1. Introduction; 2. Linear Regression Models; 3. Nonlinear Regression Models; 4. Logistic Regression Models; 5. Model Evaluation and Selection; 6. Discriminant Analysis; 7. Bayesian Classification; 8. Support Vector Machines; 9. Principal Component Analysis; 10. Clustering; A. Bootstrap Methods; B. Lagrange Multipliers; C. EM Algorithm; Bibliography.
Series Title: Chapman & Hall/CRC Texts in Statistical Science.

Abstract:

""The presentation is always clear and several examples and figures facilitate an easy understanding of all the techniques. The book can be used as a textbook in advanced undergraduate courses in multivariate analysis, and can represent a valuable reference manual for biologists and engineers working with multivariate datasets.""--Fabio Rapallo, Zentralblatt MATH 1296.

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Select the Optimal Model for Interpreting Multivariate DataIntroduction to Multivariate Analysis: Linear and Nonlinear Modeling shows how multivariate analysis is widely used for extracting useful Read more...

 
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