Matrix Tricks for Linear Statistical Models : Our Personal Top Twenty

Simo Puntanen

ISBN 10: 364210472X / ISBN 13: 9783642104725

Published by Springer, Springer Vieweg, 2011

About this Item

Druck auf Anfrage Neuware - Printed after ordering - In teaching linear statistical models to first-year graduate students or to final-year undergraduate students there is no way to proceed smoothly without matrices and related concepts of linear algebra; their use is really essential. Our experience is that making some particular matrix tricks very familiar to students can substantially increase their insight into linear statistical models (and also multivariate statistical analysis). In matrix algebra, there are handy, sometimes even very simple 'tricks' which simplify and clarify the treatment of a problem-both for the student and for the professor. Of course, the concept of a trick is not uniquely defined-by a trick we simply mean here a useful important handy result.In this book we collect together our Top Twenty favourite matrix tricks for linear statistical models.

Seller Inventory # 9783642104725

Bibliographic Details

• Title: Matrix Tricks for Linear Statistical Models : Our Personal Top Twenty
• Publisher: Springer, Springer Vieweg
• Publication Date: 2011
• Language: English
• ISBN 10: 364210472X
• ISBN 13: 9783642104725
• Binding: Buch
• Condition: Neu
• Dimensions: 241W x 160H x 32D millimeters 241 millimeters width by 160 millimeters height by 32 millimeters depth
• Weight: 916 grams

About this title

Synopsis

In teaching linear statistical models to first-year graduate students or to final-year undergraduate students there is no way to proceed smoothly without matrices and related concepts of linear algebra; their use is really essential. Our experience is that making some particular matrix tricks very familiar to students can substantially increase their insight into linear statistical models (and also multivariate statistical analysis). In matrix algebra, there are handy, sometimes even very simple “tricks” which simplify and clarify the treatment of a problem―both for the student and for the professor. Of course, the concept of a trick is not uniquely defined―by a trick we simply mean here a useful important handy result.
In this book we collect together our Top Twenty favourite matrix tricks for linear statistical models.

About the Author

Simo Puntanen earned his PhD in statistics from the University of Tampere (Tampere, Finland) in 1987, where he is now a Docent and Lecturer of Statistics. He has published over 110 research papers in matrix methods for statistics with particular emphasis on linear statistical models. He is currently the book review editor of the International Statistical Review.

George P. H. Styan earned his PhD in mathematical statistics from Columbia University in 1969 and received an Honorary PhD from the University of Tampere in 2000. He is now Professor Emeritus of Mathematics and Statistics at McGill University in  Montreal, Canada. He has published over 140 research papers, mostly in matrix methods for statistics, and since 2005, his main interests have focused on magic squares, and mathematical and statistical philately.

Jarkko Isotalo earned his PhD in statistics from the University of Tampere (Tampere, Finland) in 2007, where he is now a Lecturer of Statistics. His main research interests have been linear statistical models, matrix methods for statistics, and computational statistics. He is currently also doing applied research on statistical genetics.

Puntanen, Styan, and Isotalo, knowing just what is expected of authors, would like to agree with P. G. Wodehouse and apologize for childhoods that were as normal as rice-pudding and lives that consisted of little more than sitting in front of the laptop and cursing a bit.