Multivariate Statistics: Old School: Mathematical and methodological introduction to multivariate statistical analytics, including linear model (Paperback) (ISBN-13: 9781456538835)

Multivariate Statistics: Old School is a mathematical and methodological introduction to multivariate statistical analysis. It presents the basic mathematical grounding that graduate statistics students need for future research, and important multivariate techniques useful to statisticians in general. The material provides support for further study in big data and machine learning.

Topics include

• The multivariate normal and Wishart distributions
• Linear models, including multivariate regression and analysis of variance, and both-sides models (GMANOVA, repeated measures, growth curves)
• Linear algebra useful for multivariate statistics
• Covariance structures, including principal components, factor analysis, independence and conditional independence, and symmetry models
• Classification (linear and quadratic discrimination, trees, logistic regression)
• Clustering (K-means, model-based, hierarchical)
• Other techniques, including biplots, canonical correlations, and multidimensional scaling

Most of the analyses in the book use the statistical computing environment R, for which there is an available package (msos) of multivariate routines and data sets.

This text was developed over many years by the author, John Marden, while teaching in the Department of Statistics, University of Illinois at Urbana-Champaign.

Author: John I. Marden
ISBN-10: 1456538837
ISBN-13: 9781456538835
Publisher: Createspace Independent Publishing Platform
Language: English
Published: 09/14/2015
Pages: 360
Format: Paperback
Weight: 1.06lbs
Size: 9.02h x 5.98w x 0.75d