mle2 from package bbmle gives non-sensical answers

I want to fit some field data with a custom-made negative exponential probability density function. (Motivation- I eventually want to fit the field data to many of the distributions in table 3 of Bullock Shea and Skarpaas 2006).

First I defined a dnegexp function according to this post: Error with custom density function definition for mle2 formula call

dnegexp <- function(x, mya, myb, log=FALSE){
   logne <- log(mya)-myb*x
   if(log) return(logne) else return(exp(logne))
}

Then I made an rnegexp function that generates a dataset from this distribution with any given parameters. (Please forgive the inelegance of this function- it is not the topic of this post, but ideas to make it better are welcome...)

rnegexp <- function(n, thisa, thisb){
  rnums <- array(data=NA,dim=n)
  counter=0
  while(counter<=n){
    candidate <- runif(1,0,100)
    if(runif(1,0,1)<dnegexp(candidate,thisa, thisb)) {
      rnums[counter] <- candidate
      counter <- counter+1
    }
  }
  return(rnums)
}

With those two functions in hand, I test my workflow by creating a dataset that follows the negative exponential distribution with known parameters:

set.seed(501)
mynegexpvals <- rnegexp(100,0.08, 0.09)

hist(mynegexpvals, freq=FALSE)
mydists <- seq(0,100, by=1)
lines(mydists,dnegexp(mydists, 0.08, 0.09), col="blue", lwd=2)

When I try to use mle2 from the bbmle package to find the parameters, it gives non-sensical values, even though I gave it the exact generating parameters as starting values:

> library(bbmle)
> mle2(mynegexpvals ~ dnegexp(a,b), start = list(a=0.08, b=0.09), data=data.frame(mynegexpvals))

Call:
mle2(minuslogl = mynegexpvals ~ dnegexp(a, b), start = list(a = 0.08, 
    b = 0.09), data = data.frame(mynegexpvals))

Coefficients:
            a             b 
 2.421577e+12 -6.849330e+12 

Log-likelihood: 6.148807e+15

Attempts to bound the search space yields parameter estimates at the boundary:

> mle2(mynegexpvals ~ dnegexp(a,b), start = list(a=0.08, b=0.09), data=data.frame(mynegexpvals), method="L-BFGS-B", lower=c(a=0.04, b=0.0001), upper=c(a=1000, b=1000))

Call:
mle2(minuslogl = mynegexpvals ~ dnegexp(a, b), start = list(a = 0.08, 
    b = 0.09), method = "L-BFGS-B", data = data.frame(mynegexpvals), 
    lower = c(a = 0.04, b = 1e-04), upper = c(a = 1000, b = 1000))

Coefficients:
    a     b 
1e+03 1e-04 

Log-likelihood: 690.69 
Warning message:
In mle2(mynegexpvals ~ dnegexp(a, b), start = list(a = 0.08, b = 0.09),  :
  some parameters are on the boundary: variance-covariance calculations based on Hessian may be unreliable

Am I missing something major here? Did I define my dnegexp function wrong?