Overdispersion in count data regression is often caused by neglection or inappropriate modelling of individual heterogeneity, temporal or spatial correlation, and nonlinear covariate effects. In this paper, we develop and study semiparametric count data models which can deal with these issues by...

Abstract In this paper a cold standby system consisting of two identical components (first component in working state and second one in the cold standby state) and one repairman is studied. A replacement policy is considered which is based on the number of down times in a renewal cycle. The...

In many cases of modeling bivariate count data, the interest lies on studying the association rather than the marginal properties. We form a flexible regression copula-based model where covariates are used not only for the marginal but also for the copula parameters. Since copula measures the...

Sequence data from a series of homologous DNA segments from related organisms are typically polymorphic at many sites, and these polymorphisms are the result of evolutionary processes. Such data may be used to estimate the substitution rates as well as the variability of these rates. Careful...

In this paper we extend Rydberg-Shephards acivity, direction and size decomposition of trade-by-trade price movements to the mulvariate case. We illustrate our ideas using a bivariate modelling problem - modelling the evolution of the prices of Ford and GM shares. Throughout we use the...