dlmRandom function

Random DLM

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)

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?

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.

Returns

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.

References

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

Author(s)

Giovanni Petris GPetris@uark.edu

See Also

dlm

Examples

dlmRandom(1, 3, 5)