dlmModARMA {dlm} | R Documentation |
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. |
m0 |
m0, the expected value of the pre-sample state vector. |
C0 |
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 GPetris@uark.edu
Giovanni Petris (2010), An R Package for Dynamic Linear
Models. Journal of Statistical Software, 36(12), 1-16.
http://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.
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))