Abstract. Time series of counts arise when the interest lies on the number of certain events occurring during a specified time interval. Many of these data sets are characterized by low counts, asymmetric distributions, excess zeros, over dispersion, ruling out normal approximations. Several approaches and diversified models that explicitly account for the discreteness of the data have been con...

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 Poisson distribution.

In this paper we introduce a simple bivariate integer-valued time series model with positively correlated geometric marginals based on the negative binomial thinning mechanism. Some properties of the model are considered. The unknown parameters of the model are estimated using the modified conditional least squares method. © 2011 Elsevier Ltd. All rights reserved.

BACKGROUND Increased electrical activity in peripheral sensory neurons including dorsal root ganglia (DRG) and trigeminal ganglia neurons is an important mechanism underlying pain. Voltage gated sodium channels (VGSC) contribute to the excitability of sensory neurons and are essential for the upstroke of action potentials. A unique type of VGSC current, resurgent current (INaR), generates an in...

: Idiopathic nonallergic rhinitis (iNAR) has been difficult to define because of the long differential diagnosis of rhinopathy in the absence of allergic rhinitis. iNAR has traditionally been a diagnosis of exclusion with no clear unifying pathophysiology. Increased sensitivity to triggers such has climate changes, cold air, tobacco smoke, strong odors, and perfumes have been thought to be char...

In this paper the integer-valued autoregressive model of order one, contaminated with additive or innovational outliers is studied in some detail, parameter estimation is also addressed. In particular, the asymptotic behavior of conditional least squares (CLS) estimators is analyzed. We suppose that the time points of the outliers are known, but their sizes are unknown. It is proved that the CL...

In this paper, we propose a queueing model based on an integer-valued rst-order autoregressive(INAR(1)) process. We derive the queue length distribution and its asymptotic decay rate of the proposed model. Also, our numerical study shows that the new model can be considered as an alternative approach to the well-known MMPP=D=1 queue in terms of performance and amount of computational work. c © ...

The high-order statistics (moments and cumulants of order higher than two) have been widely applied in several fields, specially in problems where it is conjectured a lack of Gaussianity and/or non-linearity. Since the INteger-valued AutoRegressive, INAR, models are non-Gaussian, the high-order statistics can provide additional information that allows a better characterization of these processe...