Matrix Algebra: Theory, Computations and Applications in Statistics (Springer Texts in Statistics) - Softcover

Críticas

“Gentle has put in a lot of time and effort to writing this book with careful attention to details. ... it is all needed to make sure the student has a firm and solid understanding of matrix algebra on the graduate level. I would recommend this book for all those who teach graduate level matrix algebra or ... to those undergraduate students who wish to have an independent study.” (Peter Olszewski, MAA Reviews, January, 2018)

“Beautifully written, easy to read, with a well subindexed index of 16 pages and a bibliography of 13 that includes most modern and relevant textbooks and articles in the area of matrix theory and computations, as well as for statistics and big data computations.” (Frank Uhlig, zbMATH 1386.15002, 2018)

“This very reader-friendly written volume presents an opportunity to graduate students and researchers to enjoy reading on the classical matrix analysis in its modern applications to statistics and to implement these methods in practical problem solving.” (Stan Lipovetsky, Technometrics, Vol. 60 (2), 2018)

Reseña del editor

This much-needed work presents, among other things, the relevant aspects of the theory of matrix algebra for applications in statistics. Written in an informal style, it addresses computational issues and places more emphasis on applications than existing texts.