Estimation Of A Dynamic Linear Model
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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.
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.
Adaptive Estimation Of The Dynamic Linear Model With Fixed Effects
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Author : Tiemen Woutersen
language : en
Publisher:
Release Date : 2002
Adaptive Estimation Of The Dynamic Linear Model With Fixed Effects written by Tiemen Woutersen and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with categories.
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.
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.
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.
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.
Further Developments In The Estimation Of Dynamic Linear Statistical Models
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Author : R. D. Snyder
language : en
Publisher:
Release Date : 1985
Further Developments In The Estimation Of Dynamic Linear Statistical 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 1985 with Linear models (Statistics) categories.
The Econometrics Of Panel Data
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Author : László Mátyás
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-12-01
The Econometrics Of Panel Data written by László Mátyás 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 2013-12-01 with Business & Economics categories.
The aim of this volume is to provide a general overview of the econometrics of panel data, both from a theoretical and from an applied viewpoint. Since the pioneering papers by Edwin Kuh (1959), Yair Mundlak (1961), Irving Hoch (1962), and Pietro Balestra and Marc Nerlove (1966), the pooling of cross sections and time series data has become an increasingly popular way of quantifying economic relationships. Each series provides information lacking in the other, so a combination of both leads to more accurate and reliable results than would be achievable by one type of series alone. Over the last 30 years much work has been done: investigation of the properties of the applied estimators and test statistics, analysis of dynamic models and the effects of eventual measurement errors, etc. These are just some of the problems addressed by this work. In addition, some specific diffi culties associated with the use of panel data, such as attrition, heterogeneity, selectivity bias, pseudo panels etc., have also been explored. The first objective of this book, which takes up Parts I and II, is to give as complete and up-to-date a presentation of these theoretical developments as possible. Part I is concerned with classical linear models and their extensions; Part II deals with nonlinear models and related issues: logit and pro bit models, latent variable models, duration and count data models, incomplete panels and selectivity bias, point processes, and simulation techniques.
Optimal Estimation Of Dynamic Systems
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Author : John L. Crassidis
language : en
Publisher: CRC Press
Release Date : 2004-04-27
Optimal Estimation Of Dynamic Systems written by John L. Crassidis and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-04-27 with Mathematics categories.
Most newcomers to the field of linear stochastic estimation go through a difficult process in understanding and applying the theory.This book minimizes the process while introducing the fundamentals of optimal estimation. Optimal Estimation of Dynamic Systems explores topics that are important in the field of control where the signals receiv