Paul Hudson <paulhudson028 <at> gmail.com> writes:
>
> Hello all,
>
> I want to fit a tweedie distribution to the data I have.
>
> The R packages I have been able to find assume that I want to use it as
> part as of a generalized linear model.
>
> This is not the case, I want to directly fit the distribution to the data.
>
> Is there a package that allows this?
This took a little bit of fussing but it seems OK:
library("tweedie")
set.seed(1001)
r <- rtweedie(1000,1.5,mu=2,phi=2)
library("bbmle")
dtweedie2 <- function(x,power,mu,phi,log=FALSE,debug=FALSE) {
if (debug) cat(power,mu,phi,"\n")
res <- dtweedie(y=x,xi=power,mu=mu,phi=phi)
if (log) log(res) else res
}
m <- mle2(r~dtweedie2(power=exp(logpower),
mu=exp(logmu),
phi=exp(logphi)),
## don't start with logpower=0 (power=1)
start=list(logpower=0.1,logmu=0,logphi=0),
data=data.frame(r),
method="Nelder-Mead")
dtweedie2(r,xi=exp(0.1),mu=1,phi=1)
In principle MASS::fitdistr could be made to work too.
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