[R] invalid function value in 'nlm' optimizer

[William Dunlap]

Your function ln() does not return a scalar.
   > ln(theta=c(1,2))
   [1] 48.5342640972 48.5342640972 48.5342640972 48.5342640972 48.5342640972


Bill Dunlap
TIBCO Software
wdunlap tibco.com

On Tue, Apr 28, 2015 at 6:40 PM, Hanze Zhang <kevin511511 at gmail.com> wrote:

> I still cannot solve the problem:  'invalid function value in 'nlm'
> optimizer'
>
> I want to get the MLE for theta[1] and theta[2], my code is below:
>
>
> x <- c(2,5,3,7,3,2,4)
> delta <- c(1, 0, 1, 1, 1, 0, 1)
>
> # -log likelihood
> #alpha<-theta[1]
> #lamda<-theta[2]
> ln<-function(theta,x1,x2  )
>   {
>
>
>  -sum(delta)*log(theta[1]*theta[2])-sum(delta)*(theta[1]-1)*log(x[delta==1])+theta[2]*sum(x^theta[1])
> }
>
>
> #MLE
> nlm(ln,theta<-c(1,1),x1=x, x2=delta, hessian=TRUE)
>
>
> On Tue, Apr 28, 2015 at 6:40 AM, Duncan Murdoch <murdoch.duncan at gmail.com>
> wrote:
>
> > On 28/04/2015 2:43 AM, Hanze Zhang wrote:
> > > Hi, R users,
> > >
> > >
> > > I am using nlm function to get the MLE of parameter alpha and lambda
> > from a
> > >  parametric survival model (Weibull distribution). However, this
> message
> > > always came out: ' invalid function value in 'nlm' optimizer'. Could
> > anyone
> > > help me? Code is
> > >
> > > project<-read.table(file="C://data.txt", header=T, as.is=T)
> > > names(project)
> > > attach(project)
> > >
> > > x<-time
> > > delta<-ind
> > >
> > >
> > > # -log likelihood
> > > #alpha<-theta[1]
> > > #lambda<-theta[2]
> > > ln<-function(theta)
> > >   {
> > >
> > >
> >
> -sum(delta)*log(theta[1]*theta[2])-sum(delta)*(theta[1]-1)*log(x[delta==1])+theta[2]*sum(x^theta[1])
> > > }
> > >
> > > #MLE
> > > nlm(ln,theta<-c(1,1),hessian=TRUE)
> >
> > You are taking logs of parameters.  Probably the optimizer is setting
> > the parameters to negative values, and so the log returns NaN.
> >
> > You can avoid this by testing your parameters on input, and always
> > returning a valid number.  There are lots of ways to do this: One
> > strategy is to return +Inf for invalid values; another is to move the
> > parameter to the nearest boundary, and apply a penalty according to how
> > far you moved it.  Or just take the absolute value of the parameter.  Or
> > reparametrize so that illegal values aren't possible.
> >
> > Duncan Murdoch
> >
> >
>
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>
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