Create a DLM representation of an ARMA process
The function creates an object of class dlm representing a specified univariate or multivariate ARMA process
dlmModARMA(ar = NULL, ma = NULL, sigma2 = 1, dV, m0, C0)
ar
: a vector or a list of matrices (in the multivariate case) containing the autoregressive coefficients.
ma
: a vector or a list of matrices (in the multivariate case) containing the moving average coefficients.
sigma2
: the variance (or variance matrix) of the innovations.
dV
: the variance, or the diagonal elements of the variance matrix in the multivariate case, of the observation noise. V
is assumed to be diagonal and it defaults to zero.
m0
: , the expected value of the pre-sample state vector.
C0
: , the variance matrix of the pre-sample state vector.
The returned DLM only gives one of the many possible representations of an ARMA process.
The function returns an object of class dlm representing the ARMA model specified by ar
, ma
, and sigma2
.
Giovanni Petris (2010), An R Package for Dynamic Linear Models. Journal of Statistical Software, 36(12), 1-16. https://www.jstatsoft.org/v36/i12/.
Petris, Petrone, and Campagnoli, Dynamic Linear Models with R, Springer (2009).
Durbin and Koopman, Time series analysis by state space methods, Oxford University Press, 2001.
Giovanni Petris GPetris@uark.edu
dlmModPoly
, dlmModSeas
, dlmModReg
## ARMA(2,3) dlmModARMA(ar = c(.5,.1), ma = c(.4,2,.3), sigma2=1) ## Bivariate ARMA(2,1) dlmModARMA(ar = list(matrix(1:4,2,2), matrix(101:104,2,2)), ma = list(matrix(-4:-1,2,2)), sigma2 = diag(2))
Useful links