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R: dlmMLE usage

More than 5 years have passed since last update.

This is the tool to help us with the M step.
This is connected to optim, so we can use that as well.
We are still using the model

x_0 ~ N(m0, C0) 
x_t = GG x_{t-1} + w_t v_t ~ N(0, W)
Y_t = FF x_t + v_t w_t ~ N(0, V)

function dlmMLE

Input: 

Data:
    The time series data.

Parameters: 
    The parameters subject to the Likelihood optimization

build:
    function that returns a dlm object. That is, 
    build=function(x) will make the objective       function the likelihood function of the dlm governed by parameter x. 

Example:

buildTest <- function(x){ 
    m <- dlmModPoly(1, dV = exp(x[1]))
    m$JW  <- matrix(1)
    m$X <- matrix(exp(x[2]), nc = 1, nr = length(Nile))
    j <- which(time(Nile) == 1899)
m$X[j,1] <- m$X[j,1] * (1+ exp(x[3]))
return(m)    
}

buildTest will give me dlm dependent on three parameters, in which W is given by
exp(x[2])*(1+ exp(x[3])).

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