How to estimate parameters from BG / NBD model using bbmle? - r

Question

I am trying to estimate the probability for a customer to be alive after a certain period. I have data for 500 customers of a firm. For each customer I know x (number of transactions by a given customer over all time periods), tx (time of the last transaction) and T (total time between the first purchase and the end of the observation window).
I work with the BG/NBD model. In order to estimate the probability to be alive, I first need to estimate 4 parameters (r, alpha, a and b) included in this model. To optimize the value of these parameters, I am using the « bbmle » package (shown below).
However when I run the code, it doesn’t give any result. Furthermore it also seems that R doesn’t recognise many of the « objects » that are included in the functions below.
Does anyone notice any error that I’ve made in the code ? Is there another way to write it ?
bgLlh <- function(mydata, r, alpha, a, b) {
with (mydata, {
if (a<=0 | b<=0 | r<=0 | alpha<=0) return (NaN)
term1 <-log(gamma(r+mydata$x)) - log(gamma(r)) + r*log(alpha)
term2 <-log(gamma(a+b))+log(gamma(b+mydata$x))-log(gamma(b))-log(gamma(a+b+mydata$x))
term3<- -(r+mydata$x)*log(alpha+mydata$T)
term4 <- if(mydata$x > 1) {log(a)-log(b+mydata$x-1)-(r+mydata$x)*log(alpha+mydata$tx)
} else {0}
llh <- term1 + term2 +log(exp(term3)+(mydata$x>0)*exp(term4))
f <- -sum(llh)
return(f)
})
}
bgEstimateParameters <- function(mydata, initValues, safeMode=FALSE) {
llhd <- function(r, alpha, a, b) {
return (bgLlh(data, r, alpha, a, b))
}
library(bbmle)
if (safeMode) {
fit <- mle2(llhd, initValues, skip.hessian=TRUE, method="Nelder-Mead")
} else {
fit <- mle2(llhd, initValues)
}
return (fit)
}