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Package KFAS provides funchtions for Kalman filtering, state, disturbance and simulation smoothing, forecasting and simulation of state space models. All functions can use exact diffuse initialisation when distributions of some or all elements of initial state vector are unknown. Filtering, state smoothing and simulation functions use sequential processing algorithm, which is faster than standard approach, and it also allows singularity of prediction error variance matrix. KFAS also contains function for computing the likelihood of exponential family state space models and function for state smoothing of exponential family state space models. WWW: http://cran.r-project.org/web/packages/KFAS/
13 lines
702 B
Plaintext
13 lines
702 B
Plaintext
Package KFAS provides funchtions for Kalman filtering, state,
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disturbance and simulation smoothing, forecasting and simulation
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of state space models. All functions can use exact diffuse
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initialisation when distributions of some or all elements of initial
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state vector are unknown. Filtering, state smoothing and simulation
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functions use sequential processing algorithm, which is faster than
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standard approach, and it also allows singularity of prediction
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error variance matrix. KFAS also contains function for computing
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the likelihood of exponential family state space models and function
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for state smoothing of exponential family state space models.
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WWW: http://cran.r-project.org/web/packages/KFAS/
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