Recursive Estimation Of Dynamic Linear Models
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Recursive Estimation Of Dynamic Linear Models
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Author : R. D. Snyder
language : en
Publisher:
Release Date : 1984
Recursive Estimation Of Dynamic Linear Models written by R. D. Snyder and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1984 with Regression analysis categories.
Recursive Estimation And Time Series Analysis
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Author : Peter C. Young
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-08-04
Recursive Estimation And Time Series Analysis written by Peter C. Young and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-08-04 with Technology & Engineering categories.
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.
Recursive Estimation And Time Series Analysis
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Author : Peter C. Young
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Recursive Estimation And Time Series Analysis written by Peter C. Young and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Technology & Engineering categories.
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.
Recursive Models Of Dynamic Linear Economies
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Author : Lars Peter Hansen
language : en
Publisher: Princeton University Press
Release Date : 2018-07-10
Recursive Models Of Dynamic Linear Economies written by Lars Peter Hansen and has been published by Princeton University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-10 with Business & Economics categories.
A guide to the economic modeling of household preferences, from two leaders in the field A common set of mathematical tools underlies dynamic optimization, dynamic estimation, and filtering. In Recursive Models of Dynamic Linear Economies, Lars Peter Hansen and Thomas Sargent use these tools to create a class of econometrically tractable models of prices and quantities. They present examples from microeconomics, macroeconomics, and asset pricing. The models are cast in terms of a representative consumer. While Hansen and Sargent demonstrate the analytical benefits acquired when an analysis with a representative consumer is possible, they also characterize the restrictiveness of assumptions under which a representative household justifies a purely aggregative analysis. Hansen and Sargent unite economic theory with a workable econometrics while going beyond and beneath demand and supply curves for dynamic economies. They construct and apply competitive equilibria for a class of linear-quadratic-Gaussian dynamic economies with complete markets. Their book, based on the 2012 Gorman lectures, stresses heterogeneity, aggregation, and how a common structure unites what superficially appear to be diverse applications. An appendix describes MATLAB programs that apply to the book's calculations.
Dynamic Linear Models With R
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Author : Giovanni Petris
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-06-12
Dynamic Linear Models With R written by Giovanni Petris and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-06-12 with Mathematics categories.
State space models have gained tremendous popularity in recent years in as disparate fields as engineering, economics, genetics and ecology. After a detailed introduction to general state space models, this book focuses on dynamic linear models, emphasizing their Bayesian analysis. Whenever possible it is shown how to compute estimates and forecasts in closed form; for more complex models, simulation techniques are used. A final chapter covers modern sequential Monte Carlo algorithms. The book illustrates all the fundamental steps needed to use dynamic linear models in practice, using R. Many detailed examples based on real data sets are provided to show how to set up a specific model, estimate its parameters, and use it for forecasting. All the code used in the book is available online. No prior knowledge of Bayesian statistics or time series analysis is required, although familiarity with basic statistics and R is assumed.
Estimation Of A Dynamic Linear Model
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Author : R. D. Snyder
language : en
Publisher:
Release Date : 1985
Estimation Of A Dynamic Linear Model written by R. D. Snyder and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1985 with Linear models (Statistics) categories.
Modelling And Parameter Estimation Of Dynamic Systems
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Author : J.R. Raol
language : en
Publisher: IET
Release Date : 2004-08-13
Modelling And Parameter Estimation Of Dynamic Systems written by J.R. Raol and has been published by IET this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-08-13 with Mathematics categories.
This book presents a detailed examination of the estimation techniques and modeling problems. The theory is furnished with several illustrations and computer programs to promote better understanding of system modeling and parameter estimation.
Theory And Practice Of Recursive Identification
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Author : Lennart Ljung
language : en
Publisher: MIT Press (MA)
Release Date : 1985
Theory And Practice Of Recursive Identification written by Lennart Ljung and has been published by MIT Press (MA) this book supported file pdf, txt, epub, kindle and other format this book has been release on 1985 with Mathematics categories.
This book provides a comprehensive and systematic framework for developing, describing, and analyzing such recursive algorithms.
Estimation Of A Dynamic Linear Model With Unknown Starting Values
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Author : R. D. Snyder
language : en
Publisher:
Release Date : 1986
Estimation Of A Dynamic Linear Model With Unknown Starting Values written by R. D. Snyder and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1986 with Algebras, Linear categories.
Compstat
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Author : F. de Antoni
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Compstat written by F. de Antoni and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Business & Economics categories.
When dealing with the design or with the application of any technical system, which is not quite simple and trivial, one has to face to the problem to determine the allowable de viations of the system functions and the optimal vector of system parameter tolerances. The need for the solution of this problem is stimulated with various serious economic and maite nance aspects, between them the tendency to reach the minimal production cost, the maximal system operation reliability are the most frequent. Suppose that we are dealing with an system S, consisting of N components represented by the system parame ters xi' i = 1, 2 . . . N, which are arranged in certain structu re so, that the K, system functions F k' k = 1, 2 . . . IG , expres sing the considered system properties, fullfil the condition F-FO~ AF, /1/ \'Ihere F = l F k} Ie is the set of the actual system functions, FO = lFOk}~ is the set of the nominal system functions and A F = l A F k 1(;. } is the set 0 f the a 11 0 w a b 1 e s emf y s t u n c ion t s de viations. The set F depends besides the system structure also on the vector X = [Xi}N of the system parameters. Suppose, that the system structure is invariant.