Recursive Estimation and Time-Series Analysis

1. Front Matter

   Pages i-xv

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2. Introduction

   1. Introduction

      • Peter Young

      Pages 1-7

3. Recursive Parameter Estimation

   1. Front Matter

      Pages 8-8

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   2. Recursive Estimation: A Tutorial Introduction

      • Peter Young

      Pages 9-23

   3. Recursive Estimation and Stochastic Approximation

      • Peter Young

      Pages 24-41

   4. Recursive Least Squares Regression Analysis

      • Peter Young

      Pages 42-54

   5. Recursive Estimation of Time-Variable Parameters in Regression Models

      • Peter Young

      Pages 55-102

4. Recursive Time-Series Analysis

   1. Front Matter

      Pages 103-103

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   2. The Time-Series Estimation Problem

      • Peter Young

      Pages 104-128

   3. The Instrumental Variable (IV) Method of Time-Series Analysis

      • Peter Young

      Pages 129-167

   4. Optimum Instrumental Variable Methods of Time-Series Model Estimation

      • Peter Young

      Pages 168-204

   5. Alternative Recursive Approaches to Time-Series Analysis

      • Peter Young

      Pages 205-230

   6. Recursive Estimation: A General Tool in Data Analysis and Stochastic Model Building

      • Peter Young

      Pages 231-240

   7. Epilogue

      • Peter Young

      Pages 241-244

5. Back Matter

   Pages 245-300

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This book has grown out of a set of lecture notes prepared originally for a NATO Summer School on "The Theory and Practice of Systems ModelLing and Identification" held between the 17th and 28th July, 1972 at the Ecole Nationale Superieure de L'Aeronautique et de L'Espace. Since this time I have given similar lecture courses in the Control Division of the Engineering Department, University of Cambridge; Department of Mechanical Engineering, University of Western Australia; the University of Ghent, Belgium (during the time I held the IBM Visiting Chair in Simulation for the month of January, 1980), the Australian National University, and the Agricultural University, Wageningen, the Netherlands. As a result, I am grateful to all the reci­ pients of these lecture courses for their help in refining the book to its present form; it is still far from perfect but I hope that it will help the student to become acquainted with the interesting and practically useful concept of recursive estimation. Furthermore, I hope it will stimulate the reader to further study the theoretical aspects of the subject, which are not dealt with in detail in the present text. The book is primarily intended to provide an introductory set of lecture notes on the subject of recursive estimation to undergraduate/Masters students. However, the book can also be considered as a "theoretical background" handbook for use with the CAPTAIN Computer Package.

• Analysis
• Matlab
• Normal
• STATISTICA
• algorithms
• control
• data analysis
• filters
• information
• linear regression
• linearity
• measurement
• regression analysis
• statistics
• system

• University of Lancaster, Lancaster, Lancs., England

  Peter Young

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