[R] Error in optim function.

Rolf Turner rolf.turner at xtra.co.nz
Tue Sep 27 06:40:19 CEST 2011


(a) This is pretty obviously homework; the r-help list is *not* for
giving help with homework.

(b) *Read* the error message!

(c) Your expression for the log likelihood is wrong in more than
one way.  (The number of observations is *not* the same thing
as the number of trials for a given observation.)

     cheers,

         Rolf Turner

On 27/09/11 15:33, jango wrote:
> I'm trying to calculate the maximum likelihood estimate for a binomial
> distribution.  Here is my code:
>
> y<- c(2, 4, 2, 4, 5, 3)
> n<- length(y)
> binomial.ll<- function (pi, y, n) {        ## define log-likelihood
>    output<- y*log(pi)+(n-y)*(log(1-pi))
>    return(output)
> }
> binomial.mle<- optim(0.01,                     ## starting value
>                       binomial.ll,               ## log likelihood
>                       method="BFGS",             ## optimization method
>                       hessian=TRUE,              ## numerial Hessian
>                       control=list(fnscale=-1),  ## max, not min
>                       y=y, n=n)
> binomial.mle.par<- c(binomial.mle$par, -1/binomial.mle$hessian[1,1])
> binomial.mle.par<- as.matrix(binomial.mle.par)
> rownames(binomial.mle.par)<- c("lambda", "s.e.")
> colnames(binomial.mle.par)<- c("MLE")
> print(binomial.mle.par)
>
> When I do this I get the following error message:
>
> Error in optim(0.01, binomial.ll, method = "BFGS", hessian = TRUE, control =
> list(fnscale = -1),  :
>    objective function in optim evaluates to length 6 not 1
>
> Any help you can give me would be greatly appreciated.
>
> --
> View this message in context: http://r.789695.n4.nabble.com/Error-in-optim-function-tp3846001p3846001.html
> Sent from the R help mailing list archive at Nabble.com.
>
> ______________________________________________
> R-help at r-project.org mailing list
> 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.
>



More information about the R-help mailing list