Introduction to multivariate analysis linear and nonlinear modeling

"Multivariate techniques are used to analyze data that arise from more than one variable in which there are relationships between the variables. Mainly based on the linearity of observed variables, these techniques are useful for extracting information and patterns from multivariate data as wel...

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Bibliographic Details
Main Author: Konishi, Sadanori (Author)
Format: Book
Language:English
Published: Boca Raton, FL CRC Press is an imprint of Taylor & Francis Group, an Informa Business 2014
Series:Chapman & Hall/CRC Texts in Statistical Science
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245 1 0 |a Introduction to multivariate analysis  |b linear and nonlinear modeling  |c Sadanori Konishi 
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505 0 |a 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 
520 |a "Multivariate techniques are used to analyze data that arise from more than one variable in which there are relationships between the variables. Mainly based on the linearity of observed variables, these techniques are useful for extracting information and patterns from multivariate data as well as for the understanding the structure of random phenomena. This book describes the concepts of linear and non-linear" 
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