State Space Methods in RATS

This paper uses several examples to show how the econometrics program RATS can be used to analyze state space models. It demonstrates Kalman filtering and smoothing, estimation of hyperparameters, unconditional and conditional simulation. It also provides a more complicated example where a dynamic s...

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Main Author: Thomas Doan
Format: Article
Language:English
Published: Foundation for Open Access Statistics 2011-05-01
Series:Journal of Statistical Software
Subjects:
Online Access:http://www.jstatsoft.org/v41/i09/paper
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spelling doaj-1edb48d8c6f14ea58810b1e6d4dcad4f2020-11-24T20:53:42ZengFoundation for Open Access StatisticsJournal of Statistical Software1548-76602011-05-014109State Space Methods in RATSThomas DoanThis paper uses several examples to show how the econometrics program RATS can be used to analyze state space models. It demonstrates Kalman filtering and smoothing, estimation of hyperparameters, unconditional and conditional simulation. It also provides a more complicated example where a dynamic simultaneous equations model is transformed into a proper state space representation and its unknown parameters are estimated.http://www.jstatsoft.org/v41/i09/paperARMA modelKalman filterstate space methodsunobserved componentssoftware tools
collection DOAJ
language English
format Article
sources DOAJ
author Thomas Doan
spellingShingle Thomas Doan
State Space Methods in RATS
Journal of Statistical Software
ARMA model
Kalman filter
state space methods
unobserved components
software tools
author_facet Thomas Doan
author_sort Thomas Doan
title State Space Methods in RATS
title_short State Space Methods in RATS
title_full State Space Methods in RATS
title_fullStr State Space Methods in RATS
title_full_unstemmed State Space Methods in RATS
title_sort state space methods in rats
publisher Foundation for Open Access Statistics
series Journal of Statistical Software
issn 1548-7660
publishDate 2011-05-01
description This paper uses several examples to show how the econometrics program RATS can be used to analyze state space models. It demonstrates Kalman filtering and smoothing, estimation of hyperparameters, unconditional and conditional simulation. It also provides a more complicated example where a dynamic simultaneous equations model is transformed into a proper state space representation and its unknown parameters are estimated.
topic ARMA model
Kalman filter
state space methods
unobserved components
software tools
url http://www.jstatsoft.org/v41/i09/paper
work_keys_str_mv AT thomasdoan statespacemethodsinrats
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