Elements of Statistical Computing : NUMERICAL COMPUTATION

R. A. Thisted

ISBN 10: 0412013711 / ISBN 13: 9780412013713

Published by Routledge, 1988

About this Item

nach der Bestellung gedruckt Neuware - Printed after ordering - Statistics and computing share many close relationships. Computing now permeates every aspect of statistics, from pure description to the development of statistical theory. At the same time, the computational methods used in statistical work span much of computer science. Elements of Statistical Computing covers the broad usage of computing in statistics. It provides a comprehensive account of the most important computational statistics. Included are discussions of numerical analysis, numerical integration, and smoothing.The author give special attention to floating point standards and numerical analysis; iterative methods for both linear and nonlinear equation, such as Gauss-Seidel method and successive over-relaxation; and computational methods for missing data, such as the EM algorithm. Also covered are new areas of interest, such as the Kalman filter, projection-pursuit methods, density estimation, and other computer-intensive techniques.

Seller Inventory # 9780412013713

Bibliographic Details

• Title: Elements of Statistical Computing : NUMERICAL COMPUTATION
• Publisher: Routledge
• Publication Date: 1988
• Language: English
• ISBN 10: 0412013711
• ISBN 13: 9780412013713
• Binding: Buch
• Condition: Neu
• Dimensions: 240W x 161H x 29D millimeters 240 millimeters width by 161 millimeters height by 29 millimeters depth
• Weight: 834 grams

About this title

Synopsis

Statistics and computing share many close relationships. Computing now permeates every aspect of statistics, from pure description to the development of statistical theory. At the same time, the computational methods used in statistical work span much of computer science. Elements of Statistical Computing covers the broad usage of computing in statistics. It provides a comprehensive account of the most important computational statistics. Included are discussions of numerical analysis, numerical integration, and smoothing. The author give special attention to floating point standards and numerical analysis; iterative methods for both linear and nonlinear equation, such as Gauss-Seidel method and successive over-relaxation; and computational methods for missing data, such as the EM algorithm. Also covered are new areas of interest, such as the Kalman filter, projection-pursuit methods, density estimation, and other computer-intensive techniques.

About the Author

R.A. Thisted