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We investigate joint temporal and contemporaneous aggregation of N independent copies of strictly stationary INteger-valued AutoRegressive processes of order 1 (INAR(1)) with random coefficient $\alpha\in(0,1)$ and with idiosyncratic…

Probability · Mathematics 2021-10-19 Matyas Barczy , Fanni K. Nedényi , Gyula Pap

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 $\alpha \in (0, 1)$ and idiosyncratic…

Probability · Mathematics 2016-01-19 Fanni Nedényi , Gyula Pap

We discuss joint temporal and contemporaneous aggregation of $N$ independent copies of AR(1) process with random-coefficient $a \in [0,1)$ when $N$ and time scale $n$ increase at different rate. Assuming that $a$ has a density, regularly…

Statistics Theory · Mathematics 2013-10-23 Vytaute Pilipauskaite , Donatas Surgailis

An inhomogeneous first--order integer--valued autoregressive (INAR(1)) process is investigated, where the autoregressive type coefficient slowly converges to one. It is shown that the process converges weakly to a Poisson or a compound…

Probability · Mathematics 2007-06-13 László Györfi , Márton Ispány , Gyula Pap , Katalin Varga

We discuss joint temporal and contemporaneous aggregation of $N$ independent copies of random-coefficient AR(1) process driven by i.i.d. innovations in the domain of normal attraction of an $\alpha$-stable distribution, $0< \alpha \le 2$,…

Statistics Theory · Mathematics 2020-05-01 Vytautė Pilipauskaitė , Viktor Skorniakov , Donatas Surgailis

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

Probability · Mathematics 2015-10-01 Richard C. Bradley

In this paper, we introduce the first-order integer-valued autoregressive (INAR(1)) model, with Poisson-Lindley innovations based on power series thinning operator. Some mathematical features of this process are given and estimating the…

Applications · Statistics 2018-10-08 Eisa Mahmoudi , Ameneh Rostami , Rasool Roozegar

In this paper, we present a fractional decomposition of the probability generating function of the innovation process of the first-order non-negative integer-valued autoregressive [INAR(1)] process to obtain the corresponding probability…

Methodology · Statistics 2020-07-27 Josemar Rodrigues , Marcelo Bourguignon , Manoel Santos-Neto , N. Balakrishnan

We discuss contemporaneous aggregation of independent copies of a triangular array of random-coefficient AR(1) processes with i.i.d. innovations belonging to the domain of attraction of an infinitely divisible law W. The limiting aggregated…

Statistics Theory · Mathematics 2013-07-09 Anne Philippe , Donata Puplinskaite , Donatas Surgailis

The random coefficient integer-valued autoregressive process was introduced by Zheng, Basawa, and Datta. In this paper we study the asymptotic behavior of this model (in particular, weak limits of extreme values and the growth rate of…

Probability · Mathematics 2012-04-17 Zheng Zhong , Alexander Roitershtein

INteger Auto-Regressive (INAR) processes are usually defined by specifying the innovations and the operator, which often leads to difficulties in deriving marginal properties of the process. In many practical situations, a major modeling…

Methodology · Statistics 2020-04-21 Matheus B. Guerrero , Wagner Barreto-Souza , Hernando Ombao

Existing integer-valued autoregressive (INAR) models for count random fields suffer from difficulties in characterizing the stationary marginal distribution and in computing conditional probabilities (as required for likelihood inference).…

Methodology · Statistics 2026-05-15 Christian H. Weiß , Angelika Silbernagel

A new integer--valued autoregressive process (INAR) with Generalised Lagrangian Katz (GLK) innovations is defined. This process family provides a flexible modelling framework for count data, allowing for under and over--dispersion,…

Methodology · Statistics 2024-12-18 Ovielt Baltodano Lopez , Federico Bassetti , Giulia Carallo , Roberto Casarin

INAR (integer-valued autoregressive) and INGARCH (integer-valued GARCH) models are among the most commonly employed approaches for count time series modelling, but have been studied in largely distinct strands of literature. In this paper,…

Probability · Mathematics 2024-04-05 Johannes Bracher , Barbora Sobolová

For each $\lambda>0$ and every square-integrable infinitely-divisible (ID) distribution there exists at least one stationary stochastic process $t\mapsto X_t$ with the specified distribution for $X_1$ and with first-order autoregressive…

Probability · Mathematics 2021-06-02 Robert L Wolpert

In this paper, we investigate the scaling limit of heavy-tailed nearly unstable cumulative INAR($\infty$) processes. These processes exhibit a power-law tail of the form $n^{-(1+\alpha)}$ for $\alpha \in (\frac{1}{2}, 1)$, and the $\ell^1$…

Probability · Mathematics 2026-02-17 Yingli Wang , Chunhao Cai , Ping He , QingHua Wang

An extension of the RINAR(1) process for modelling discrete-time dependent counting processes is considered. The model RINAR(p) investigated here is a direct and natural extension of the real AR(p) model. Compared to classical INAR(p)…

Methodology · Statistics 2009-02-11 M. Kachour

We study an iterated temporal and contemporaneous aggregation of $N$ independent copies of a strongly stationary subcritical Galton-Watson branching process with regularly varying immigration having index $\alpha \in (0, 2)$. Limits of…

Probability · Mathematics 2020-12-09 Matyas Barczy , Fanni K. Nedényi , Gyula Pap

Contemporaneous aggregation of individual AR(1) random processes might lead to different properties of the limit aggregated time series, in particular, long memory (Granger, 1980). We provide a new characterization of the series of…

Statistics Theory · Mathematics 2015-08-11 Bernard Candelpergher , Michel Miniconi , Florian Pelgrin

We consider a time-varying first-order autoregressive model with irregular innovations, where we assume that the coefficient function is H\"{o}lder continuous. To estimate this function, we use a quasi-maximum likelihood based approach. A…

Statistics Theory · Mathematics 2023-02-28 Hanna Gruber , Moritz Jirak
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