Introduction to Multivariate Analysis - Linear and Nonlinear Modeling

This text shows how to use multivariate analysis to extract useful information from multivariate data and understand the structure of random phenomena. Along with the basic concepts of various procedures in traditional multivariate analysis, the book covers nonlinear techniques for clarifying phenomena behind observed multivariate data. It prima

List of contents

Introduction. Linear Regression Models. Nonlinear Regression Models. Logistic Regression Models. Model Evaluation and Selection. Discriminant Analysis. Bayesian Classification. Support Vector Machines. Principal Component Analysis. Clustering. Appendices. Bibliography. Index.

About the author

Sadanori Konishi

Summary

This text shows how to use multivariate analysis to extract useful information from multivariate data and understand the structure of random phenomena. Along with the basic concepts of various procedures in traditional multivariate analysis, the book covers nonlinear techniques for clarifying phenomena behind observed multivariate data. It prima

Product details

• Authors: Sadanori Konishi, Sadanori (Chuo University Konishi, Konishi Sadanori
• Publisher: Taylor & Francis Ltd.
• Languages: English
• Product format: Paperback / Softback
• Released: 30.06.2020
• EAN: 9780367576134
• ISBN: 978-0-367-57613-4
• No. of pages: 338
• Series: Chapman & Hall/CRC Texts in Statistical Science
• Subjects: Humanities, art, music > Psychology > Basic principles; Natural sciences, medicine, IT, technology > Mathematics > Probability theory, stochastic theory, mathematical statistics; MATHEMATICS / Probability & Statistics / General, Biology, life sciences, Psychological methodology, Probability & statistics, Probability and statistics