KimSmoother2: Smoothing algorithm from Kim (1994) to be used following a...
In SebKrantz/dynfacto_R: Dynamic Factor Model Estimation for Nowcasting
Description
Usage
Arguments
Value
Description
Smoothing algorithm from Kim (1994) to be used following a run
of KimFilter function.
Usage
1
KimSmoother2(xA, Pa, A, P, x, p, stateP, stateP_fut)
Arguments
xA
Filtered state vector to be smoothed
Pa
Filtered state covariance to be smoothed
A
Array with transition matrices
P
State-dependent state covariance
x
State-dependent state vector
p
Markov transition matrix
stateP
Evolving current probability matrix
stateP_fut
Predicted probability matrix
Value
Smoothed states and covariance matrices. This is the equivalent
of Kalman smoother in Markov-switching case.
SebKrantz/dynfacto_R documentation built on Dec. 31, 2020, 4:30 p.m.
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Description Usage Arguments Value
Description
Smoothing algorithm from Kim (1994) to be used following a run of KimFilter function.
Usage
1 | KimSmoother2(xA, Pa, A, P, x, p, stateP, stateP_fut)
|
Arguments
xA |
Filtered state vector to be smoothed |
Pa |
Filtered state covariance to be smoothed |
A |
Array with transition matrices |
P |
State-dependent state covariance |
x |
State-dependent state vector |
p |
Markov transition matrix |
stateP |
Evolving current probability matrix |
stateP_fut |
Predicted probability matrix |
Value
Smoothed states and covariance matrices. This is the equivalent of Kalman smoother in Markov-switching case.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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