Finite mixture of tweedie - r

Question

I'm trying to estimate a finite mixture of tweedie (or compound Poisson-gamma) distributions. I have scoured any resources I can think of, without finding any resources on how to do this.
I am currently trying to use the flexmix package in R writing a different M-step driver, as outlined in the flexmix vignette on pages 12-14. Here is my code, which relies on the cplm package:
tweedieClust <- function(formula = .~.,offset = NULL){
require(tweedie)
require(cplm)
require(plyr)
require(dplyr)
retval <- new("FLXMC", weighted = TRUE, formula = formula, dist = "tweedie",
name = "Compound Poisson Clustering")
retval#defineComponent <- expression ({
predict <- function(x, ...) {
pr <- mu
}
logLik <- function(x, y, ...){
dtweedie(y, xi = p, mu = mu, phi = phi) %>%
log
}
new("FLXcomponent",
parameters=list(coef=coef),
logLik=logLik, predict=predict,
df=df)
})
retval#fit <- function (x, y, w, component) {
fit <- cpglm(formula = y ~ x, link = "log", weights=w, offset=offset)
with(list(coef = coef(fit), df = ncol(x),mu = fit$fitted.values,
p = fit$p, phi = fit$phi),
eval(retval#defineComponent))
}
retval
}
However, this results in the following error:
Error in dtweedie(y, xi = p, mu = mu, phi = phi) :
binary operation on non-conformable arrays
Has anyone done or seen a finite mixture of tweedie distributions? Can you point me in the right direction to accomplish this, using flexmix or otherwise?

Answer 1

The problem is somewhere in the weights part, if you remove it, it works:
tweedieClust <- function(formula = .~.,offset = NULL){
require(tweedie)
require(statmod)
require(cplm)
require(plyr)
require(dplyr)
retval <- new("FLXMC", weighted = F, formula = formula, dist = "tweedie",
name = "Compound Poisson Clustering")
retval#defineComponent <- expression ({
predict <- function(x, ...) {
pr <- mu
}
logLik <- function(x, y, ...){
dtweedie(y, xi = p, mu = mu, phi = phi) %>%
log
}
new("FLXcomponent",
parameters=list(mu=mu,xi=p,phi=phi),
logLik=logLik, predict=predict,
df=df)
})
retval#fit <- function (x, y, w, component) {
fit <- cpglm(formula = End~.,data=dmft, link = "log")
with(list(df = ncol(x), mu = fit$fitted.values,
p = fit$p, phi = fit$phi),
eval(retval#defineComponent))
}
retval
}
example:
library(flexmix)
data("dmft", package = "flexmix")
m1 <- flexmix(End ~ .,data=dmft, k = 4, model = tweedieClust())