init_kf: Initialization of Kalman filter
In tfarima: Transfer Function and ARIMA Models
init_kf R Documentation
Initialization of Kalman filter
Description
init_kf computes the starting values x0 and P0 by generalized least
squares using the first n observations.
Usage
init_kf(mdl, z = NULL, n = 0)
Arguments
mdl
an object of class ssm.
z
optional time series if it differs from model series.
n
integer, number of observations used to estimate the initial
conditions. If n < d (dimension of state vector), it defaults to length(z).
Value
A list with components:
x0
initial state vector estimate
P0
covariance matrix of the initial state estimate
tfarima documentation built on Nov. 5, 2025, 7:43 p.m.
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| init_kf | R Documentation |
Initialization of Kalman filter
Description
init_kf computes the starting values x0 and P0 by generalized least
squares using the first n observations.
Usage
init_kf(mdl, z = NULL, n = 0)
Arguments
mdl |
an object of class |
z |
optional time series if it differs from model series. |
n |
integer, number of observations used to estimate the initial conditions. If n < d (dimension of state vector), it defaults to length(z). |
Value
A list with components:
x0 |
initial state vector estimate |
P0 |
covariance matrix of the initial state estimate |
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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