[PDF] Optimal Instrumental Variables Estimation For Arma Models eBook

Author : Kenneth D. West
Publisher :
Page : 30 pages
File Size : 34,15 MB
Release : 2000
Category : Estimation theory
ISBN :

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In many time series models, an infinite number of moments can be used for estimation in a large sample. I supply a technically undemanding proof of a condition for optimal instrumental variables use of such moments in a parametric model. I also illustrate application of the condition in estimation of a linear model with a conditionally heteroskedastic disturbance.

Author : Mohamed Najim
Publisher :
Page : 424 pages
File Size : 16,9 MB
Release : 2008
Category : Electric filters, Digital
ISBN :

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The purpose of this book is to provide graduate students and practitioners with traditional methods and more recent results for model-based approaches in signal processing. Firstly, discrete-time linear models such as AR, MA and ARMA models, their properties and their limitations are introduced. In addition, sinusoidal models are addressed. Secondly, estimation approaches based on least squares methods and instrumental variable techniques are presented. Finally, the book deals with optimal filters, i.e. Wiener and Kalman filtering, and adaptive filters such as the RLS, the LMS and their variants.

Author : P. C. B. Phillips
Publisher : Cambridge University Press
Page : 390 pages
File Size : 38,23 MB
Release : 2006-01-09
Category : Business & Economics
ISBN : 9780521807234

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The essays in this book explore important theoretical and applied advances in econometrics.

Author : Peter C. Young
Publisher : Springer Science & Business Media
Page : 505 pages
File Size : 30,40 MB
Release : 2011-08-04
Category : Technology & Engineering
ISBN : 3642219810

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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 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 MatlabTM 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.

Author : Mohamed Najim
Publisher : John Wiley & Sons
Page : 410 pages
File Size : 10,68 MB
Release : 2010-01-05
Category : Technology & Engineering
ISBN : 0470393688

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The purpose of this book is to provide graduate students and practitioners with traditional methods and more recent results for model-based approaches in signal processing. Firstly, discrete-time linear models such as AR, MA and ARMA models, their properties and their limitations are introduced. In addition, sinusoidal models are addressed. Secondly, estimation approaches based on least squares methods and instrumental variable techniques are presented. Finally, the book deals with optimal filters, i.e. Wiener and Kalman filtering, and adaptive filters such as the RLS, the LMS and their variants.