Basics of Matrix Algebra for Statistics With R

Avoiding vector spaces and other advanced mathematics, this book shows how to manipulate matrices and perform numerical calculations in R. It provides a guide to elementary matrix algebra sufficient for undertaking specialized courses, such as multivariate data analysis and linear models. It also covers advanced topics, such as generalized inverses of singular and rectangular matrices and manipulation of partitioned matrices, for those who want to delve deeper into the subject. The text includes many numerical examples as well as theoretical and numerical exercises.

List of contents

Introduction. Vectors and Matrices. Rank of Matrices. Determinants. Inverses. Eigenanalysis of Real Symmetric Matrices. Vector and Matrix Calculus. Further Topics. Key Applications to Statistics. Outline Solutions to Exercises. Bibliography. Index.

About the author

Dr. Nick Fieller is a retired senior lecturer in the School of Mathematics and Statistics and an honorary research fellow in archaeology at the University of Sheffield. His research interests include multivariate data analysis and statistical modeling in the pharmaceutical industry, archaeology, and forensic sciences.

Product details

• Authors: Nick Fieller, Nick (University of Sheffield Fieller, Fieller Nick
• Publisher: Taylor & Francis Ltd.
• Languages: English
• Product format: Hardback
• Released: 06.07.2015
• EAN: 9781498712361
• ISBN: 978-1-4987-1236-1
• No. of pages: 244
• Series: Chapman & Hall/CRC The R Series
• Subjects: Natural sciences, medicine, IT, technology > Mathematics > Arithmetic, algebra; MATHEMATICS / Probability & Statistics / General, MATHEMATICS / Algebra / General, Mathematics