On 22-11-2012, at 22:55, Дмитрий Островский wrote:
> I am trying to optimize custom likelyhood with nlminb()
> Arguments h and f are meant to be fixed.
>
> example.R:
>
> compute.hyper.log.likelyhood <- function(a, h, f) {
> a1 <- a[1]
> a2 <- a[2]
> l <- 0.0
> for (j in 1:length(f)) {
> l <- l + lbeta(a1 + f[j], a2 + h - f[j]) - lbeta(a1, a2)
> }
> return(l)
> }
>
> compute.optimal.hyper.params <- function(start, limits, h_, f_) {
> result <- nlminb(start,
> compute.hyper.log.likelyhood,
> h=h_,
> f=f_,
> scale = -1,
> lower = c(limits[1],limits[1]),
> upper = c(limits[2],limits[2]))
> return (result[[1]])
> }
>
> Console launch:
>
> source('~/Desktop/Dropbox/example.R')
> h <- 1000
> start <- c(3,3)
> limits <- c(0.01,100)
> f <- c(40,30,50)
> compute.optimal.hyper.params(start,limits,h,f)
>
>
> produces the following:
>
> Error in a2 + h : 'h' is missing
>
>
> Could you please explain me why?
You appear to being bitten by partial argument matching.
See section 8.1.20 of the R inferno
(http://www.burns-stat.com/pages/Tutor/R_inferno.pdf).
Either call nlminb with an explicit hessian=NULL or change the name of argument
h in compute.hyper.log.likelyhood to something else such as hv.
Berend
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