kfks_cpp: Kalman filter smoother
In juhokalle/rmfd4dfm: Estimation of DFMs using RMFD-E parametrization
kfks_cpp R Documentation
Kalman filter smoother
Description
Kalman filter smoother
Usage
kfks_cpp(A, C, R, Q, data_wide, P1, dim_state, only_ll)
Arguments
A
n x r observation system matrix
C
r x r state transition matrix
R
n x n noise covariance matrix
Q
q x q error covariance matrix
data_wide
n x T data matrix
P1
r x r initial state variance matrix
dim_state
value r
only_ll
boolean, return only log-likelihood calculated with KFss
juhokalle/rmfd4dfm documentation built on July 18, 2024, 10:19 p.m.
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.
| kfks_cpp | R Documentation |
Kalman filter smoother
Description
Kalman filter smoother
Usage
kfks_cpp(A, C, R, Q, data_wide, P1, dim_state, only_ll)
Arguments
A |
n x r observation system matrix |
C |
r x r state transition matrix |
R |
n x n noise covariance matrix |
Q |
q x q error covariance matrix |
data_wide |
n x T data matrix |
P1 |
r x r initial state variance matrix |
dim_state |
value r |
only_ll |
boolean, return only log-likelihood calculated with KFss |
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.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.