Generate a random (constant or time-varying) object of class
"dlm"
, along with states and observations from it.
dlmRandom(m, p, nobs = 0, JFF, JV, JGG, JW)
The function returns a list with the following components.
An object of class "dlm"
.
Matrix of simulated state vectors from the model.
Matrix of simulated observations from the model.
If nobs
is zero, only the mod
component is returned.
dimension of the observation vector.
dimension of the state vector.
number of states and observations to simulate from the model.
should the model have a time-varying FF
component?
should the model have a time-varying V
component?
should the model have a time-varying GG
component?
should the model have a time-varying W
component?
Giovanni Petris GPetris@uark.edu
The function generates randomly the system and observation matrices and
the variances of a DLM having the specified state and observation
dimension. The system matrix GG
is guaranteed to have
eigenvalues strictly less than one, which implies that a constant DLM is
asymptotically stationary. The default behavior is to generate a
constant DLM. If JFF
is TRUE
then a model for
nobs
observations in which all
the elements of FF
are time-varying is generated. Similarly
with JV
, JGG
, and JW
.
Anderson and Moore, Optimal filtering, Prentice-Hall (1979)
dlm