Hi,

 

I’m trying to estimate different parameters in an alternative wrapped Cauchy
distribution (where mu (mui) is dependent on several variables (such as c, z
and mu0), where c is a constant) and using the following log-likelihood and
MLE functions:

 

###log likelihood for  wrapped cauchy ###

wrappedCauchy.lik<-function(theta,y,x,z){

n<-nrow(y)

 

mu0 <- theta[1]

rho <- theta[2]

c <- theta[3]

mui <- mu0+(x-mu0)*(1-exp(-c*z))

 

logl<-sum(log((1-(rho^2))/(1+(rho^2)-2*rho*cos(y-mui))/(2*pi)))

return(-logl)

}

 

##Method for MLE###

d <- optim(c(mu0,rho0, 2.3),wrappedCauchy.lik,y=turn1,x = HRturns1, z =
HRDistance1, method="CG")

 

 

The problem here is that the optim results are equal to the initial values
and therefore changes dependent on those values – am I doing something wrong
here?

When I run a simpler version of the wrapped cauchy – just estimating mu and
rho (without mu being dependent on c), the optim estimates seem to work as
the are different from the initial values. Is it a problem trying to get MLE
for a constant – in this case c?

 

Thanks

Lene

 

___________________________

Lene Jung Kjær

Studsdalvej 20, Taulov

7000 Fredericia, Danmark

Tlf: 29 86 96 14

email: ljkjar@hotmail.com 




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