Sandra Dias
CEMAT e Dep. de Matemática, Universidade de Trás-os-Montes e Alto Douro
In this talk, we will present a bivariate max-INAR(1) model that is an extension of the univariate model studied in Scotto et al. (2018). Considering a bivariate geometric distribution for the innovations, we establish asymptotic lower and upper bounds for the limiting behaviour of the bivariate maximum of the proposed model. In the max-semistable context, we obtain the limiting distribution of the bivariate maximum, when the number of variables in each margin has a geometric growing pattern.
This is a join work with Maria da Graça Temido.
References
[1] Scotto, M.G., Weiss, C.H, Möller, T.A., Gouveia, S. The max-
INAR(1) model for count processes. Test, 27, 850–870, 2018. https://doi.org/10.1007/s11749-017-0573-z