The function returns the MLE of unknown parameters in the specification of a state space model.
1 
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

method 
passed to 
... 
additional arguments passed to 
debug 
if 
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
.
The build
argument must return a dlm with nonsingular
observation variance V
.
Giovanni Petris GPetris@uark.edu
Giovanni Petris (2010), An R Package for Dynamic Linear
Models. Journal of Statistical Software, 36(12), 116.
http://www.jstatsoft.org/v36/i12/.
Petris, Petrone, and Campagnoli, Dynamic Linear Models with
R, Springer (2009).
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42  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")]

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