On weak dependence conditions for Poisson autoregressions

By Paul Doukhan, Konstantinos Fokianos, Dag Tjøstheim. 2012

124 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Finance, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/8efbc693a1d265b891c45ae346c240e4486df3ef

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

In Finance

In Statistics and Probability

Citations in the corpus

Parameter Change Test for Poisson Autoregressive Models (2014, background): “Recently, Doukhan et al. (2012) showed the existence of a strictly stationary ergodic solution for model (2.1) with finite moments of any order.”
Theory and inference for a class of nonlinear models with application to time series of counts (2016, background): “…the linear assumption on the Poisson INGARCH to a general contracting evolution rule and proved the absolute regularity for this Poisson count process, and Doukhan, Fokianos, and Tjøstheim (2012) showed the existence of moments under similar conditions by utilizing the concept of weak dependence.”
Theory and Inference for a Class of Observation-driven Models with Application to Time Series of Counts (2012, background): “…Neumann (2011) relaxed the linear assumption to a general contracting evolution rule and proved the absolute regularity for this Poisson count process and Doukhan et al. (2012) showed the existence of moments under similar conditions by utilizing the concept of weak dependence.”
QUASI‐LIKELIHOOD INFERENCE FOR NEGATIVE BINOMIAL TIME SERIES MODELS (2013, background): “…(Haggan and Ozaki, 1981) f .y1; 1/ D d C a1 C c1 exp 21 C b1y1; (6) and assuming that d; a1; c1; b1; > 0; see Fokianos and Tjøstheim (2012) and Doukhan et al. (2012) who studied in detail the preceding model by either employing an approximation lemma or the notion of weak…”
Ergodicity of observation-driven time series models and consistency of the maximum likelihood estimator (2012, methodology): “We do not follow the weak dependence approach which as outlined in Doukhan et al. (2012) also implies unnecessary Lipshitz assumptions of the model and does not yield directly a theory for likelihood inference.”
Count Time Series: A Methodological Review (2021, background): “Series properties are established in Neumann (2011), Doukhan, Fokianos, and Tjøstheim (2012), and Douc, Doukhan, and Moulines (2013).”
Self-Excited Threshold Poisson Autoregression (2013, methodology): “n, also known as the Poisson integer-valued GARCH (INGARCH), has already received considerable study in the literature, see for example, Ferland et al. (2006), Fokianos et al. (2009), Neumann (2011), Doukhan et al. (2012), Davis and Liu (2012), and Fokianos and Tjøstheim (2012). For this model, it i”