A copula-based bivariate integer-valued autoregressive process with application

A bivariate first-order signed integer-valued autoregressive process

Stationary solutions for integer-valued autoregressive processes

The purpose of this paper is to introduce and develop a family of Z+-valued autoregressive processes of order p (INAR(p)) by using the generalized multiplication F of van Harn and Steutel (1982). We obtain various distributional and regression properties for these models. A number of stationary INAR(p) processes with specific marginals are presented and are shown to generalize several existing ...

Estimating Bivariate Tail: a copula based approach

This paper deals with the problem of estimating the tail of a bivariate distribution function. To this end we develop a general extension of the POT (PeaksOver-Threshold) method, mainly based on a two-dimensional version of the Pickands-Balkema-de Haan Theorem. We introduce a new parameter that describes the nature of the tail dependence, and we provide a way to estimate it. We construct a two-...

A parametric study for the first-order signed integer-valued autoregressive process

In recent years, many attempts have been made to find accurate models for integer-valued times series. The SINAR (for Signed INteger-valued AutoRegressive) process is one of the most interesting. Indeed, the SINAR model allows negative values both for the series and its autocorrelation function. In this paper, we focus on the simplest SINAR(1) model under some parametric assumptions. Explicitly...

Copula bivariate probit models: with an application to medical expenditures.

The bivariate probit model is frequently used for estimating the effect of an endogenous binary regressor (the 'treatment') on a binary health outcome variable. This paper discusses simple modifications that maintain the probit assumption for the marginal distributions while introducing non-normal dependence using copulas. In an application of the copula bivariate probit model to the effect of ...