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.
--
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(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.
>
> ______________________________________________
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> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
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 > >After defining your binomial.ll function do this binomial.ll(0.01,y,n) and you will see that your function is returning a vector of length 6, which is the length of y. Your function is returning a vector but should return a scalar. A likelihood is a scalar so maybe return(sum(output)). Berend -- View this message in context: http://r.789695.n4.nabble.com/Error-in-optim-function-tp3846001p3846179.html Sent from the R help mailing list archive at Nabble.com.