Hi Ravi,
I have generated some random variable from generalised gamma distribution,
and now I need to use them to test on my optim function. Please see below:
*##Need to install package VGAM first before calling rggamma function
library(VGAM)
x <- rggamma(500,scale=gamma(1.5)/gamma(3.5),d=0.5,k=1.5)
mlogl <- function(param){
n <- length(x)
psi <- numeric(n)
psi[1] <- 1.0
a0 <- param[1]; a1 <-param[2]; b1 <- param[3]; alpha <- param[4]; kappa <-
param[5];
for (i in 2:n) {
psi[i] <- a0 + a1*x[i-1] + b1*psi[i-1]
lam <- gamma(kappa)/gamma(kappa+(1/alpha))
ll <-
n*log(alpha/gamma(kappa))+kappa*alpha*sum(log(x))-kappa*alpha*sum(log(psi*lam))-lam^(-alpha)*sum((x/psi)^alpha)
}
return(-ll)
}
fittedparam<-optim(c(0.1,0.05,0.5,0.65,1.8),mlogl,x)*
While I do need to put some constrains on my parameters,* the parameters
param[1]~param[5] all need to be positive*. Do you know how to have this
done?
Thank you!
Carol
On Fri, May 7, 2010 at 11:12 PM, Ravi Varadhan <rvarad...@jhmi.edu> wrote:
> It probably means that your parameters are taking on values that are
> infeasible. You may have to impose constraints on your parameters to get a
> solution (e.g. bounds constraints). If you need better help, you have to
> send us a minimal, self-contained, reproducible example.
>
> Ravi.
>
> -----Original Message-----
> From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org]
> On
> Behalf Of Carol Gao
> Sent: Friday, May 07, 2010 5:53 AM
> To: R-help@r-project.org
> Subject: [R] problem in using optim
>
> Dear R users,
>
> When I was trying to use the function *optim* to get the MLEs, quite a few
> warning messages showed up as below:
>
> Warning in log(psi * lam) : NaNs produced
>
> I am just wondering what does this mean? Was it something wrong with my
> likelihood function or was it sth wrong with the data?
>
> Thanks in advance.
>
> Carol Gao
>
> [[alternative HTML version deleted]]
>
> ______________________________________________
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> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
>
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