English

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

Probability 2018-01-19 v3

Abstract

We discuss joint temporal and contemporaneous aggregation of NN independent copies of strictly stationary INteger-valued AutoRegressive processes of order 1 (INAR(1)) with random coefficient α(0,1)\alpha\in(0,1) and with idiosyncratic Poisson innovations. Assuming that α\alpha has a density function of the form ψ(x)(1x)β\psi(x)(1 - x)^\beta, x(0,1)x\in(0,1), with limx1ψ(x)=ψ1(0,)\lim_{x\uparrow 1}\psi(x) = \psi_1 \in(0,\infty), different limits of appropriately centered and scaled aggregated partial sums are shown to exist for β(1,0)\beta\in(-1,0), β=0\beta = 0, β(0,1)\beta\in(0,1) or β(1,)\beta\in(1,\infty), when taking first the limit as NN\to\infty and then the time scale nn\to\infty, or vice versa. In fact, we give a partial solution to an open problem of Pilipauskaite and Surgailis (2014) by replacing the random-coefficient AR(1) process with a certain randomized INAR(1) process.

Keywords

Cite

@article{arxiv.1509.05149,
  title  = {Iterated limits for aggregation of randomized INAR(1) processes with Poisson innovations},
  author = {Matyas Barczy and Fanni Nedényi and Gyula Pap},
  journal= {arXiv preprint arXiv:1509.05149},
  year   = {2018}
}

Comments

49 pages. Results on centralization by the empirical mean are added

R2 v1 2026-06-22T10:58:37.781Z