On simultaneous limits for aggregation of stationary randomized INAR(1) processes with Poisson innovations

On Mixing Properties of Some INAR Models

Strictly stationary INAR(1) ("integer-valued autoregressive processes of order 1") with Poisson innovations are "interlaced rho-mixing".

Iterated limits for aggregation of randomized INAR(1) processes with Poisson innovations

We discuss joint temporal and contemporaneous aggregation of $N$ independent copies of strictly stationary INteger-valued AutoRegressive processes of order 1 (INAR(1)) with random coefficient $α\in(0,1)$ and with idiosyncratic Poisson innovations. Assuming that $α$ has a density function of the form $ψ(x)(1 - x)^β$, $x\in(0,1)$, with $\lim_{x\uparrow 1}ψ(x) = ψ_1 \in(0,\infty)$, different limits of appropriately centered and scaled aggregated partial sums are shown to exist for $β\in(-1,0)$, $β= 0$, $β\in(0,1)$ or $β\in(1,\infty)$, when taking first the limit as $N\to\infty$ and then the time …

关于新型几何与负二项INAR(1)过程

On the novel geometric and negative binomial INAR(1) processes

本文探讨新型几何与负二项INAR(1)模型的稀疏算子和已有研究的关联，证明两类模型存在性已被前向法确立，同时强化并推广了相关结果。

Stationary underdispersed INAR(1) models based on the backward approach

Most of the stationary first-order autoregressive integer-valued (INAR(1)) models were developed for a given thinning operator using either the forward approach or the backward approach. In the forward approach the marginal distribution of the time series is specified and an appropriate distribution for the innovation sequence is sought. Whereas in the backward setting, the roles are reversed. The common distribution of the innovation sequence is specified and the distributional properties of the marginal distribution of the time series are studied. In this article we focus on the backward app…

Iterated scaling limits for aggregation of random coefficient AR(1) and INAR(1) processes

We discuss joint temporal and contemporaneous aggregation of $N$ independent copies of strictly stationary AR(1) and INteger-valued AutoRegressive processes of order 1 (INAR(1)) with random coefficient $α\in (0, 1)$ and idiosyncratic innovations. Assuming that $α$ has a density function of the form $ψ(x) (1 - x)^β$, $x \in (0, 1)$, with $\lim_{x\uparrow 1} ψ(x) = ψ_1 \in (0, \infty)$, different Brownian limit processes of appropriately centered and scaled aggregated partial sums are shown to exist in case $β=1$ when taking first the limit as $N \to \infty$ and then the time scale $n \to \infty…

Change detection in INAR(p) processes against various alternative hypotheses

Change in the coefficients or in the mean of the innovation distribution of an INAR(p) process is a sign of disturbance that is important to detect. The methods of this paper can test for change in any one of these quantities separately, or in any collection of them. They are available in forms that make one-sided tests possible, furthermore, they can be used to test for a temporary change. The tests are based on a CUSUM process using conditional least squares estimators of the parameters. Under alternative hypotheses consistency of the tests is proved and the large sample properties of the ch…