… The rest of the paper is organized as follows: in Section 2 a full multivariate INAR(1) process
is introduced, with the main emphasis on the bivariate case. The method of conditional …

… The model could be seen as a revised INAR(p) process. In these two studies, some properties
of the classical statistics used in time series (sample mean, sample autocovariance and …

… In this paper a multivariate integer-valued autoregressive … Emphasis is placed on models
with periodic multivariate negative … of the conditional maximum likelihood method, a composite …

… First, we extend from a bivariate to a multivariate setting using a multivariate integer-valued
autoregressive process of order 1, MINAR(1). Second, we make use of multivariate discrete …

… Here the asymptotic distribution of the sample autocovariance for INAR ( p ) processes is
obtained and it is shown that the Yule–Walker estimator is asymptotically normally distributed, …

… time leading to multivariate time series data as, … multivariate time series models for count
data is less developed. Among the models that have been built in the context of INAR processes …

… a multivariate integer-valued autoregressive process … process, we also study two specific
parametric cases that arise under the assumptions of a multivariate Poisson and a multivariate …

… ' is intended to indicate similarity in form with the AR( p) process. … the INAR( p) process and
discuss some assumptions and peculiarities as well as the limiting distribution ofthe process. …

… Multivariate count time series data occur in many different disciplines. The class of INteger-valued
AutoRegressive (INAR) processes has the great advantage to consider explicitly both …

… Therefore, INAR-processes retain some of the … multivariate data our discussion of INAR(
1)-processes in higher dimensions are motivated by the fact that scalar INAR(M)-processes, …