The aim of these notes is to provide a guide to elementary matrix algebra sufficient for undertaking the courses on Multivariate Data Analysis and Linear Models. In fact the notes go a little further than this, providing an initial guide to more advanced topics such as generalized inverses of singular matrices and manipulation of partitioned matrices. This is to provide a first step for those who need to go a little further than just the MSc courses on Multivariate Data Analysis and Linear Models, for example when embarking on the dissertation. As well as describing the basics of matrix algebra, including numerical calculations ‘by hand’, for example of matrix multiplication and inversion, the notes give guidance on how to do numerical calculations in R and S-plus.
The following link is to the Chapman & Hall web page for the book Basics of Matrix Algebra for Statistics with R
I would be grateful for any misprints or other blunders to be brought to my attention and I will try to provide corrections here:
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|Department of Probability and Statistics||School of Mathematics and Statistics|
|This page is maintained by
Dr Nick Fieller
and was last updated on 17 August 2009.|