Kalman Filtering in R
Support in R for state space estimation via Kalman filtering was limited to one package, until fairly recently. In the last five years, the situation has changed with no less than four additional packages offering general implementations of the Kalman filter, including in some cases smoothing, simul...
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| Format: | Article |
| Language: | English |
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Foundation for Open Access Statistics
2011-03-01
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| Series: | Journal of Statistical Software |
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| Online Access: | http://www.jstatsoft.org/v39/i02/paper |
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doaj-5c7454437dcf42058650901e7159e5212020-11-25T00:11:56ZengFoundation for Open Access StatisticsJournal of Statistical Software1548-76602011-03-013902Kalman Filtering in RFernando TusellSupport in R for state space estimation via Kalman filtering was limited to one package, until fairly recently. In the last five years, the situation has changed with no less than four additional packages offering general implementations of the Kalman filter, including in some cases smoothing, simulation smoothing and other functionality. This paper reviews some of the offerings in R to help the prospective user to make an informed choice.http://www.jstatsoft.org/v39/i02/paperstate space modelsKalman filtertime seriesR |
| collection |
DOAJ |
| language |
English |
| format |
Article |
| sources |
DOAJ |
| author |
Fernando Tusell |
| spellingShingle |
Fernando Tusell Kalman Filtering in R Journal of Statistical Software state space models Kalman filter time series R |
| author_facet |
Fernando Tusell |
| author_sort |
Fernando Tusell |
| title |
Kalman Filtering in R |
| title_short |
Kalman Filtering in R |
| title_full |
Kalman Filtering in R |
| title_fullStr |
Kalman Filtering in R |
| title_full_unstemmed |
Kalman Filtering in R |
| title_sort |
kalman filtering in r |
| publisher |
Foundation for Open Access Statistics |
| series |
Journal of Statistical Software |
| issn |
1548-7660 |
| publishDate |
2011-03-01 |
| description |
Support in R for state space estimation via Kalman filtering was limited to one package, until fairly recently. In the last five years, the situation has changed with no less than four additional packages offering general implementations of the Kalman filter, including in some cases smoothing, simulation smoothing and other functionality. This paper reviews some of the offerings in R to help the prospective user to make an informed choice. |
| topic |
state space models Kalman filter time series R |
| url |
http://www.jstatsoft.org/v39/i02/paper |
| work_keys_str_mv |
AT fernandotusell kalmanfilteringinr |
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