In this paper, a first-order integer-valued autoregressive (INAR (1)) model with zero-and-one
inflated Poisson–Lindley distributed innovations is presented. It is shown that the model …

Non-negative integer-valued time series with a finite range are sometimes suffered in
environmental science, such as the weekly number of rainy-days in European cities …

The present work introduces a mixture INAR (1) model based on the mixing Pegram and
binomial thinning operators with a finite range {0, 1, ..., n\} 0, 1,…, n. The new model can be …

In this article, we propose a new seasonal geometric integer-valued autoregressive process
based on the negative binomial thinning operator with seasonal period s. Some basic …

Motivated by a large dataset containing time series of weekly number of rainy days collected
over two thousand locations across Europe and Russia for the period 2000–2010, we …

In commerce, economics, engineering and the sciences, quantitative methods based on
statistical models for forecasting are very useful tools for prediction and decision. There is an …

Many real-life count data are frequently characterized by overdispersion, excess zeros and
autocorrelation. Zero-inflated count time series models can provide a powerful procedure to …

In this paper we analyse some bootstrap techniques to make inference in INAR (p) models.
First of all, via Monte Carlo experiments we compare the performances of these methods …

In this paper, we introduce a new stationary integer-valued autoregressive process of the
first order with geometric marginal based on mixing Pegram and generalized binomial …

The main concern of this paper is providing a flexible discrete model that captures every
kind of dispersion (equi-, over-and under-dispersion). Based on the balanced discretization …