[R] About error: L-BFGS-B needs finite values of 'fn'

[ProfJCNash]

Numerical gradient approximations are being used in your call, so my
guess is that the "epsilon" has made (parameter + epsilon) an
inadmissible argument for your likelihood. If you can supply analytical
gradients, the issue has a good chance of going away. Otherwise, you'll
need to use bounds or transformations to avoid the parameter region
giving undefined results.

JN

On 15-11-07 12:12 PM, Deniz OZONUR wrote:
> Hi,
> 
> I am trying to obtain power of Likelihood ratio test for comparing gamma distribution against generalized gamma distribution. And so I need maximum likelihood estimates of Generalized gamma distribution with three parameters. I wrote code as follows.
> 
>  require(bbmle)
>  library("bbmle")
> 
> require(flexsurv)
> library("flexsurv")
> 
>  sig=0.05
>  den=1000
>  n=30
>  apar=2 ###alpha
>  bpar=3 ##beta
>  cpar=2 ##c parameter
> 
> 
>  LRatio=function(den,n,par=c(cpar,apar,bpar)){
> 
>  LR2=rep(0,den)
> 
>  count=rep(0,den)
> 
>  cpar=par[1]
>  apar=par[2]
>  bpar=par[3]
> 
>  for(i in 1:den){
> 
>  y=rgengamma.orig(n,shape=cpar,scale=bpar,k=apar)
> 
>  gamma4 = function(shape, scale) {
>   -sum(dgamma(y, shape = shape, scale = scale,log = TRUE))
>  }
> 
>  gm = mean(y)
>  cv = var(y)/mean(y)
> 
>  m5 = mle2(gamma4, start = list(shape = gm/cv, scale = cv),method = "L-BFGS-B", lower =c(.00001,.00001),upper = c(Inf,Inf))
> 
> 
>  gengamma3 = function(shape, scale,k) {
>  -sum(dgengamma.orig(y, shape = shape, scale = scale,k=k,log =TRUE))
>  }
> 
>  ci=mean(y)            #c initial value
>  a1=ci*mean(y)^(ci-1)
>  a2=ci*(ci-1)*(mean(y)^(ci-1))/2
>  mu1=mean(y)^ci+a2*mean(y^2)
>  mu2=(a1^2)*mean(y^2)+2*a1*a2*mean(y^3)+(a2^2)*(mean(y^4)-mean(y^2)^2)
>  alp =(mu1^2)/mu2                            #alpha initial value
>  bet=mean(y)*gamma(alp)/gamma(alp+(1/ci))       #beta initial value
> 
>  m6 = mle2(gengamma3, start = list(shape = ci, scale = bet, k=alp),method = "L-BFGS-B", lower = c(.00001,.00001,.00001),upper = c(Inf, Inf, nf))
> 
> 
>  LR2[i]=2*(logLik(m6)-logLik(m5))
>  count[i]=LR2[i]>=qchisq(1-sig, df=1)
> 
>  }
> 
>  pow=sum(count)/den
>  print(i)
>  print(pow)
>  }
> 
>  But I got error : optim(par = c(3.88907163215354, 3.62005456122935, 1.66499331462506 :  L-BFGS-B needs finite values of 'fn'
> 
> 
> What is wrong? Can you hep me, thanks..
> Deniz...
> 
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