\Ve present a model for data in the form of match pairs of counts. Our work is motivated by a problem in fission track analysis, where the determination of a crystal age is based on the ratio of counts of spontaneous and induced tracks. It is often reasonable to assume that the counts follow a Poisson distribution but, typically, they are overdispersed and there exists a positive correlation between the numbers of spontaneous and induced tracks at the same crystal. We propose a model that allows for both overdispersion and correlation by assuming that the mean densities follow a bivariate Wishart distribution. Our model is quite general, having the usual negative binomial or Poisson models as special cases. \Ve propose a maximum likelihood estimation method based on a stochastic implementation of the EM algorithm and we derive the asymptotic standard errors of the parameter estimates. vVe illustrate the method by a data set of fission tracks counts in matched areas of zircon crystals
