The aim of this work is the statistical modelling of counts assuming low values and exhibiting sudden and large bursts that occur randomly in time. It is well known that bilinear processes capture these kind of phenomena. In this work the integer-valued bilinear INBL(1,0,1,1) model is discussed and some properties are reviewed. Classical and Bayesian methodologies are considered and compared through simulation studies, namely to obtain estimates of model parameters and to calculate point and interval predictions. Finally, an empirical application to real epidemiological count data is also presented to attest for its practical applicability in data analysis.publishe
In this article, we introduce a class of self-exciting threshold integer-valued autoregressive model...
Non–negative integer–valued time series are often encountered in many different scientific fields, u...
In this paper the bilinear model BL(1,0,1,1) driven by exponential distributed innovations is studie...
A integer-valued bilinear type model is proposed. It can take positive as well as negative values. T...
In this paper, we extend the integer-valued model class to give a nonnegative integer-valued bilinea...
Time series of (small) counts are common in practice and appear in a wide variety of fields. In the ...
A new first-order integer-valued moving average, INMA(1), model based on the negative binomial thin...
A new first-order integer-valued moving average, INMA(1), model based on the negative binomial thinn...
Invited by Pr Konstantinos FokianosInternational audienceEconometric time series model can be define...
A bivariate autoregressive model for time series of counts is presented. The model is composed of su...
Modelling counts of events can be found in several situations of real life. For instance, the number...
Bivariate integer-valued time series occur in many areas, such as finance, epidemiology, business et...
Summary. This note reconsiders the nonnegative integer-valued bilinear processes introduced by Doukh...
International audienceWith the aim of generalizing a bilinear type counting model, we redefine a mor...
In this article, we consider two univariate random environment integer-valued autoregressive process...
In this article, we introduce a class of self-exciting threshold integer-valued autoregressive model...
Non–negative integer–valued time series are often encountered in many different scientific fields, u...
In this paper the bilinear model BL(1,0,1,1) driven by exponential distributed innovations is studie...
A integer-valued bilinear type model is proposed. It can take positive as well as negative values. T...
In this paper, we extend the integer-valued model class to give a nonnegative integer-valued bilinea...
Time series of (small) counts are common in practice and appear in a wide variety of fields. In the ...
A new first-order integer-valued moving average, INMA(1), model based on the negative binomial thin...
A new first-order integer-valued moving average, INMA(1), model based on the negative binomial thinn...
Invited by Pr Konstantinos FokianosInternational audienceEconometric time series model can be define...
A bivariate autoregressive model for time series of counts is presented. The model is composed of su...
Modelling counts of events can be found in several situations of real life. For instance, the number...
Bivariate integer-valued time series occur in many areas, such as finance, epidemiology, business et...
Summary. This note reconsiders the nonnegative integer-valued bilinear processes introduced by Doukh...
International audienceWith the aim of generalizing a bilinear type counting model, we redefine a mor...
In this article, we consider two univariate random environment integer-valued autoregressive process...
In this article, we introduce a class of self-exciting threshold integer-valued autoregressive model...
Non–negative integer–valued time series are often encountered in many different scientific fields, u...
In this paper the bilinear model BL(1,0,1,1) driven by exponential distributed innovations is studie...