add.local.level {bsts} | R Documentation |
Local level trend state component
Description
Add a local level model to a state specification. The local level model assumes the trend is a random walk:
The prior is on the
parameter.
Usage
AddLocalLevel(
state.specification,
y,
sigma.prior,
initial.state.prior,
sdy,
initial.y)
Arguments
state.specification |
A list of state components that you wish to add to. If omitted, an empty list will be assumed. |
y |
The time series to be modeled, as a numeric vector. |
sigma.prior |
An object created by |
initial.state.prior |
An object created using
|
sdy |
The standard deviation of the series to be modeled. This
will be ignored if |
initial.y |
The initial value of the series being modeled. This will be
ignored if |
Value
Returns a list with the elements necessary to specify a local linear trend state model.
Author(s)
Steven L. Scott steve.the.bayesian@gmail.com
References
Harvey (1990), "Forecasting, structural time series, and the Kalman filter", Cambridge University Press.
Durbin and Koopman (2001), "Time series analysis by state space methods", Oxford University Press.