13 research outputs found
On the theory of periodic multivariate INAR processes
In this paper a multivariate integer-valued autoregressive model of order one with
periodic time-varying parameters, and driven by a periodic innovations sequence of
independent random vectors is introduced and studied in detail. Emphasis is placed on
models with periodic multivariate negative binomial innovations. Basic probabilistic
and statistical properties of the novel model are discussed. Aiming to reduce computational burden arising from the use of the conditional maximum likelihood method, a composite likelihood-based approach is adopted. The performance of such method is
compared with that of some traditional competitors, namely moment estimators and
conditional maximum likelihood estimators. Forecasting is also addressed. Furthermore, an application to a real data set concerning the monthly number of fires in three counties in Portugal is presented.publishe