Hi,
I am having problems carrying out a mle for 3 parameters in a non-homogenous
poisson process.
I am trying to use the optim function to minimise the -ve log-likelihood.
When I use assumed values of my three parameters (20,1,1) the -ve
log-likelihood function returns a value of 1309122 but I i then use these
values as a starting point in the optim function the parameter estimates and
the function value are much lower.
Below is a summary of the output:
> optim(c(20,1,1), fn=Poisson.lik, gr=NULL, method="Nelder-Mead",w=w, t1=t1,
> t2=t2)
$par
[1] 0.004487104 -2.657468035 12.186003355
$value
[1] 289.6901
$counts
function gradient
220 NA
$convergence
[1] 0
$message
NULL
There were 50 or more warnings (use warnings() to see the first 50)
Where the warnings are:
1: In log(((theta0 * w * t2[i]) - (theta1 * cos(w * t2[i])) + ... : NaNs
produced
I thought I was using optim correctly but obviously not! Does anyone have
any suggestions as to what to try?
Thanks,
Doug
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