Without data I can't check, but try :
mle(nll,start=list(c=0.01,z=2.1,s=200),fixed=list(V=Var,M=Mean))
With a random dataset I get :
> Mean <- rnorm(136)
> Var <- 1 + rnorm(136)^2
> mle(nll,start=list(c=0.01,z=2.1,s=200),fixed=list(V=Var,M=Mean))
Error in optim(start, f, method = method, hessian = TRUE, ...) :
initial value in 'vmmin' is not finite
This might be just a data problem, but again, I'm not sure.
Cheers
Joris
On Thu, Jul 8, 2010 at 3:11 AM, Anita Narwani <anitanarw...@gmail.com> wrote:
> Hello,
> I am trying to use nlm to estimate the parameters that minimize the
> following function:
>
> Predict<-function(M,c,z){
> + v = c*M^z
> + return(v)
> + }
>
> M is a variable and c and z are parameters to be estimated.
>
> I then write the negative loglikelihood function assuming normal errors:
>
> nll<-function(M,V,c,z,s){
> n<-length(Mean)
> logl<- -.5*n*log(2*pi) -.5*n*log(s) - (1/(2*s))*sum((V-Predict(Mean,c,z))^2)
> return(-logl)
> }
>
> When I put the Mean and Variance (variables with 136 observations) into this
> function, and estimates for c,z, and s, it outputs the estimate for the
> normal negative loglikelihood given the data, so I know that this works.
>
> However, I am unable to use mle to estimate the parameters c, z, and s. I do
> not know how or where the data i.e. Mean (M) and Variance (V) should enter
> into the mle function. I have tried variations on
>
> mle(nll,start=list(c=0.01,z=2.1,s=200)) including
> mle(nll,start=list(M=Mean,V=Var, c=0.01,z=2.1,s=200))
>
> I keep getting errors and am quite certain that I just have a syntax error
> in the script because I don't know how to enter the variables into MLE.
>
> Thanks for your help,
> Anita.
>
> [[alternative HTML version deleted]]
>
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>
--
Joris Meys
Statistical consultant
Ghent University
Faculty of Bioscience Engineering
Department of Applied mathematics, biometrics and process control
tel : +32 9 264 59 87
joris.m...@ugent.be
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