Multivariate Statistical Analysis: Old School by John Marden.
From the preface:
The goal of this text is to give the reader a thorough grounding in old-school multivariate statistical analysis. The emphasis is on multivariate normal modeling and inference, both theory and implementation. Linear models form a central theme of the book. Several chapters are devoted to developing the basic models, including multivariate regression and analysis of variance, and especially the “both-sides models” (i.e., generalized multivariate analysis of variance models), which allow modeling relationships among individuals as well as variables. Growth curve and repeated measure models are special cases.
The linear models are concerned with means. Inference on covariance matrices covers testing equality of several covariance matrices, testing independence and conditional independence of (blocks of) variables, factor analysis, and some symmetry models. Principal components, though mainly a graphical/exploratory technique, also lends itself to some modeling.
Classification and clustering are related areas. Both attempt to categorize individuals. Classification tries to classify individuals based upon a previous sample of observed individuals and their categories. In clustering, there is no observed categorization, nor often even knowledge of how many categories there are. These must be estimated from the data.
Other useful multivariate techniques include biplots, multidimensional scaling, and canonical correlations.
The bulk of the results here are mathematically justified, but I have tried to arrange the material so that the reader can learn the basic concepts and techniques while plunging as much or as little as desired into the details of the proofs.
Practically all the calculations and graphics in the examples are implemented using the statistical computing environment R [R Development Core Team, 2010]. Throughout the notes we have scattered some of the actual R code we used. Many of the data sets and original R functions can be found in the file http://www.istics.net/r/multivariateOldSchool.r. For others we refer to available R packages.
This is “old school.” A preface that contains useful information and outlines what the reader may find? Definitely “old school.”
Found thanks to: Christophe Lalanne’s A bag of tweets / Feb 2012.