dlm (version 1.1-5)

dlmRandom: Random DLM

Description

Generate a random (constant or time-varying) object of class "dlm", along with states and observations from it.

Usage

dlmRandom(m, p, nobs = 0, JFF, JV, JGG, JW)

Arguments

m

dimension of the observation vector.

p

dimension of the state vector.

nobs

number of states and observations to simulate from the model.

JFF

should the model have a time-varying FF component?

JV

should the model have a time-varying V component?

JGG

should the model have a time-varying GG component?

JW

should the model have a time-varying W component?

Value

The function returns a list with the following components.

mod

An object of class "dlm".

theta

Matrix of simulated state vectors from the model.

y

Matrix of simulated observations from the model.

If nobs is zero, only the mod component is returned.

Details

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.

References

Anderson and Moore, Optimal filtering, Prentice-Hall (1979)

See Also

dlm

Examples

# NOT RUN {
dlmRandom(1, 3, 5)
# }