KalmanFilterCpp2: Implementation of a Kalman filter
In SebKrantz/dynfacto_R: Dynamic Factor Model Estimation for Nowcasting
Description
Usage
Arguments
Value
Description
Implementation of a Kalman filter
Usage
1
KalmanFilterCpp2(y, F, Q, R, A, x0, P0)
Arguments
y
Data matrix
F
Observation matrix
Q
State covariance
R
Observation covariance
A
Transition matrix
x0
Initial state vector
P0
Initial state covariance
Value
A list with estimates
SebKrantz/dynfacto_R documentation built on Dec. 31, 2020, 4:30 p.m.
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Description Usage Arguments Value
Description
Implementation of a Kalman filter
Usage
1 | KalmanFilterCpp2(y, F, Q, R, A, x0, P0)
|
Arguments
y |
Data matrix |
F |
Observation matrix |
Q |
State covariance |
R |
Observation covariance |
A |
Transition matrix |
x0 |
Initial state vector |
P0 |
Initial state covariance |
Value
A list with estimates
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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