Ebook: Recursive Estimation and Time-Series Analysis: An Introduction

This is a revised version of the 1984 book of the same name but considerably modified and enlarged to accommodate all 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 MatlabTM 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 and its other toolboxes.

The book is an introductory one on the topic of recursive estimation and itdemonstrates 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.

---

This is a revised version of the 1984 book of the same name but considerably modified and enlarged to accommodate all 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 MatlabTM 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 and its other toolboxes.

The book is an introductory one on the topic of recursive estimation and itdemonstrates 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.

Content:
Front Matter....Pages i-xv
Introduction....Pages 1-7
Front Matter....Pages 8-8
Recursive Estimation: A Tutorial Introduction....Pages 9-23
Recursive Estimation and Stochastic Approximation....Pages 24-41
Recursive Least Squares Regression Analysis....Pages 42-54
Recursive Estimation of Time-Variable Parameters in Regression Models....Pages 55-102
Front Matter....Pages 103-103
The Time-Series Estimation Problem....Pages 104-128
The Instrumental Variable (IV) Method of Time-Series Analysis....Pages 129-167
Optimum Instrumental Variable Methods of Time-Series Model Estimation....Pages 168-204
Alternative Recursive Approaches to Time-Series Analysis....Pages 205-230
Recursive Estimation: A General Tool in Data Analysis and Stochastic Model Building....Pages 231-240
Epilogue....Pages 241-244
Back Matter....Pages 245-300

---

This is a revised version of the 1984 book of the same name but considerably modified and enlarged to accommodate all 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 MatlabTM 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 and its other toolboxes.

The book is an introductory one on the topic of recursive estimation and itdemonstrates 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.

Content:
Front Matter....Pages i-xv
Introduction....Pages 1-7
Front Matter....Pages 8-8
Recursive Estimation: A Tutorial Introduction....Pages 9-23
Recursive Estimation and Stochastic Approximation....Pages 24-41
Recursive Least Squares Regression Analysis....Pages 42-54
Recursive Estimation of Time-Variable Parameters in Regression Models....Pages 55-102
Front Matter....Pages 103-103
The Time-Series Estimation Problem....Pages 104-128
The Instrumental Variable (IV) Method of Time-Series Analysis....Pages 129-167
Optimum Instrumental Variable Methods of Time-Series Model Estimation....Pages 168-204
Alternative Recursive Approaches to Time-Series Analysis....Pages 205-230
Recursive Estimation: A General Tool in Data Analysis and Stochastic Model Building....Pages 231-240
Epilogue....Pages 241-244
Back Matter....Pages 245-300
....