| dlmMLE {dlm} | R Documentation |
The function returns the MLE of unknown parameters in the specification of a state space model.
dlmMLE(y, parm, build, method = "L-BFGS-B", ..., debug = FALSE)
y |
A vector, matrix, or time series of data. |
parm |
Vector of initial values - for the optimization routine - of the unknown parameters. |
build |
A function that takes a vector of the same length as
parm and returns an object of class dlm, or a list that may
be interpreted as such. |
method |
Passed to optim. |
... |
Additional arguments passed to optim and
build. |
debug |
If TRUE, the likelihood calculations are done
entirely in R, otherwise C functions are used. |
The evaluation of the loglikelihood is done by dlmLL.
For the optimization, optim is called. It is possible for the
model to depend on additional parameters, other than those in
parm, passed to build via the ... argument.
The function dlmMLE returns the value returned by optim.
Giovanni Petris GPetris@uark.edu
data(NelPlo)
### multivariate local level -- seemingly unrelated time series
buildSu <- function(x) {
Vsd <- exp(x[1:2])
Vcorr <- tanh(x[3])
V <- Vsd %o% Vsd
V[1,2] <- V[2,1] <- V[1,2] * Vcorr
Wsd <- exp(x[4:5])
Wcorr <- tanh(x[6])
W <- Wsd %o% Wsd
W[1,2] <- W[2,1] <- W[1,2] * Wcorr
return(list(
m0 = rep(0,2),
C0 = 1e7 * diag(2),
FF = diag(2),
GG = diag(2),
V = V,
W = W))
}
suMLE <- dlmMLE(NelPlo, rep(0,6), buildSu); suMLE
buildSu(suMLE$par)[c("V","W")]
StructTS(NelPlo[,1], type="level") ## compare with W[1,1] and V[1,1]
StructTS(NelPlo[,2], type="level") ## compare with W[2,2] and V[2,2]
## multivariate local level model with homogeneity restriction
buildHo <- function(x) {
Vsd <- exp(x[1:2])
Vcorr <- tanh(x[3])
V <- Vsd %o% Vsd
V[1,2] <- V[2,1] <- V[1,2] * Vcorr
return(list(
m0 = rep(0,2),
C0 = 1e7 * diag(2),
FF = diag(2),
GG = diag(2),
V = V,
W = x[4]^2 * V))
}
hoMLE <- dlmMLE(NelPlo, rep(0,4), buildHo); hoMLE
buildHo(hoMLE$par)[c("V","W")]