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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Online Access: | http://www.jstatsoft.org/v41/i09/paper |
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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 |
_version_ |
1716796460087902208 |