4 research outputs found
Modelling overdispersion with integer-valued moving average processes
A new first-order integer-valued moving average, INMA(1), model based
on the negative binomial thinning operation defined by Risti´c et al. [21] is proposed
and characterized. It is shown that this model has negative binomial (NB) marginal
distribution when the innovations follow a NB distribution and therefore it can be
used in situations where the data present overdispersion. Additionally, this model is
extended to the bivariate context. The Generalized Method of Moments (GMM) is
used to estimate the unknown parameters of the proposed models and the results of
a simulation study that intends to investigate the performance of the method show
that, in general, the estimates are consistent and symmetric. Finally, the proposed
model is fitted to a real dataset and the quality of the adjustment is evaluated.publishe