Recursive Estimation and Time-Series Analysis: An Introduction for the Student and Practitioner

Peter C. Young

ISBN 10: 3642441297 / ISBN 13: 9783642441295

Published by Springer, 2014

About this Item

2nd edition. 524 pages. 9.25x6.10x1.19 inches. In Stock.

Seller Inventory # 3642441297

Bibliographic Details

• Title: Recursive Estimation and Time-Series Analysis: An Introduction for the Student and Practitioner
• Publisher: Springer
• Publication Date: 2014
• Language: English
• ISBN 10: 3642441297
• ISBN 13: 9783642441295
• Binding: Paperback
• Edition: 2nd Edition
• Condition: Brand New
• Weight: 0.8 kilograms

About this title

Synopsis

This is a revised version of the 1984 book of the same name but considerably modified and enlarged to accommodate the developments in recursive estimation and time series analysis that have occurred over the last quarter century. Also over this time, the CAPTAIN Toolbox for recursive estimation and time series analysis has been developed at Lancaster, for use in the Matlab^TM software environment (see Appendix G). Consequently, the present version of the book is able to exploit the many computational routines that are contained in this widely available Toolbox, as well as some of the other routines in Matlab^TM and its other toolboxes.

The book is an introductory one on the topic of recursive estimation and it demonstrates how this approach to estimation, in its various forms, can be an impressive aid to the modelling of stochastic, dynamic systems. It is intended for undergraduate or Masters students who wish to obtain a grounding in this subject; or for practitioners in industry who may have heard of topics dealt with in this book and, while they want to know more about them, may have been deterred by the rather esoteric nature of some books in this challenging area of study.

From the Back Cover

This is a revised version of the 1984 book of the same name but considerably modified and enlarged to accommodate the developments in recursive estimation and time series analysis that have occurred over the last quarter century. Also over this time, the CAPTAIN Toolbox for recursive estimation and time series analysis has been developed by my colleagues and I at Lancaster, for use in the Matlab^TM software environment (see Appendix G). Consequently, the present version of the book is able to exploit the many computational routines that are contained in this widely available Toolbox, as well as some of the other routines in Matlab^TM and its other toolboxes.

The book is an introductory one on the topic of recursive estimation and it demonstrates how this approach to estimation, in its various forms, can be an impressive aid to the modelling of stochastic, dynamic systems. It is intended for undergraduate or Masters students who wish to obtain a grounding in this subject; or for practitioners in industry who may have heard of topics dealt with in this book and, while they want to know more about them, may have been deterred by the rather esoteric nature of some books in this challenging area of study.