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I have used the stableFit function from the fBasics package to come up with parameters (alpha, beta, gamma, and delta) for a stable distribution as you can see below:

stableFit(x)

I then did the following to come up with log likelihood values and for some reason, it doesn't seem to work:

stable.fit<-function(alpha=1.387,beta=0.279,gamma=0.006948893,delta=-0.0017933)-sum(dstable(x,1.387,0.279,0.006948893,-0.0017933,pm=0,log=T))

mle.results<-mle2(stable.fit,start=list(alpha=1.387,beta=0.279,gamma=0.006948893,delta=-0.0017933),data=list(x)) #max likelihood using bbmle package

mle.results #produces the log-likelihood values

It seems that when I run the "mle.results<- mle2(.." line, R is continuously running and will not stop until I press the "STOP" button. Because of this, I am unable to then ask for the "mle.results". Why is this happening? This process seems to work fine for the normal, logistic, cauchy, student T,skewed student T, gumbell and generalized extreme value distributions.

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Looks like I was able to answer my own question. The problem was that R took a lot longer to got through the mle2 calculation along with the integration of the dstable function. Log-likelihood results took less than 10 seconds for the other distributions but for some reason, it took 45-50 minutes!! for the stable distribution. I only figured this out after I decided to just let it run while I worked on other things and after 45-50 minutes, it finished. However, I can't figure out why the stable distribution is taking exceptionally long to do this calculation. Anyway, problem solved.

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