Numerical Linear Algebra for Applications in Statistics - Couverture rigide

Gentle, James E

Couverture rigide

ISBN 10 : 0387985425 ISBN 13 : 9780387985428

Editeur : Springer-Verlag New York Inc., 1998

Synopsis

Linear algebra is one of the most imprortant mathematical and computational tools in the sciences. A knowledge of linear algebra is essential for research in statistics or the application of statistics. This book presents the aspects of numerical linear algebra that are important to statisticians.

A propos du livre

À propos de l'auteur

James E. Gentle is University Professor Emeritus at George Mason University. He is a Fellow of the American Statistical Association (ASA) and of the American Association for the Advancement of Science. He has held several national offices in the ASA and has served as associate editor of journals of the ASA, as well as for other journals in statistics and computing. He is author of Random Number Generation and Monte Carlo Methods, Computational Statistics, and Statistical Analysis of Financial Data. He is co-editor-in-chief of Wiley Interdisciplinary Reviews: Computational Statistics.

À propos de la quatrième de couverture

Numerical linear algebra is one of the most important subjects in the field of statistical computing. Statistical methods in many areas of application require computations with vectors and matrices. This book describes accurate and efficient computer algorithms for factoring matrices, solving linear systems of equations, and extracting eigenvalues and eigenvectors. Although the book is not tied to any particular software system, it describes and gives examples of the use of modern computer software for numerical linear algebra. An understanding of numerical linear algebra requires basic knowledge both of linear algebra and of how numerical data are stored and manipulated in the computer. The book begins with a discussion of the basics of numerical computations, and then describes the relevant properties of matrix inverses, matrix factorizations, matrix and vector norms, and other topics in linear algebra; hence, the book is essentially self- contained. The topics addressed in this bookconstitute the most important material for an introductory course in statistical computing, and should be covered in every such course. The book includes exercises and can be used as a text for a first course in statistical computing or as supplementary text for various courses that emphasize computations. James Gentle is University Professor of Computational Statistics at George Mason University. During a thirteen-year hiatus from academic work before joining George Mason, he was director of research and design at the world's largest independent producer of Fortran and C general-purpose scientific software libraries. These libraries implement many algorithms for numerical linear algebra. He is a Fellow of the American Statistical Association and member of the International Statistical Institute. He has held several national

Détails de l'édition

• Éditeur: Springer-Verlag New York Inc.
• Date d'édition: 1998
• Langue: anglais
• ISBN 10: 0387985425
• ISBN 13: 9780387985428
• Reliure: Relié
• Nombre de pages: 221
• Coordonnées du fabricant: Springer Nature Customer Service Center GmbH; ProductSafety@springernature.com; ; Europaplatz 3; Heidelberg; 69115; Allemagne