add.local.level | R Documentation |
Add a local level model to a state specification. The local level model assumes the trend is a random walk:
alpha[t+1] = alpha[t] + rnorm(1, 0, sigma).
The prior is on the sigma parameter.
AddLocalLevel( state.specification, y, sigma.prior, initial.state.prior, sdy, initial.y)
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 |
Returns a list with the elements necessary to specify a local linear trend state model.
Steven L. Scott steve.the.bayesian@gmail.com
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.
bsts
.
SdPrior
NormalPrior
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