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
>
>
[[alternative HTML version deleted]]
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 > > > > > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. >[[alternative HTML version deleted]]
How should I do? The issue happened on log likelihood function? On Tue, Apr 28, 2015 at 11:06 PM, William Dunlap <wdunlap at tibco.com> wrote:> 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 >> > >> > >> >> [[alternative HTML version deleted]] >> >> ______________________________________________ >> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see >> https://stat.ethz.ch/mailman/listinfo/r-help >> PLEASE do read the posting guide >> http://www.R-project.org/posting-guide.html >> and provide commented, minimal, self-contained, reproducible code. >> > >[[alternative HTML version deleted]]