The analysis of time series of counts is an emerging field of science. To obtain an ARMA-like
autocorrelation structure, many models make use of thinning operations to adapt the ARMA …

A much-needed introduction to the field of discrete-valued time series, with a focus on count-
data time series Time series analysis is an essential tool in a wide array of fields, including …

Integer-valued auto-regressive (INAR) processes have been introduced to model non-
negative integer-valued phenomena that evolve over time. The distribution of an INAR (p) …

Efficient probabilistic forecasts of integer-valued random variables are derived. The
optimality is achieved by estimating the forecast distribution non-parametrically over a given …

In this paper the asymptotic behavior of an unstable integer-valued autoregressive model of
order p (INAR (p)) is described. Under a natural assumption it is proved that the sequence of …

Discrete-valued time series are common in practice, yet methods for their analysis have
been developed only recently. The fact that the variables take values on a finite or countably …

The INteger-valued AutoRegressive (INAR) processes were introduced in the literature by.
First-order integer-valued autoregressive (INAR (1)) process. J. Time Ser. Anal. 8, 261–275] …

Replicated time series are a particular type of repeated measures, which consist of time-
sequences of measurements taken from several subjects (experimental units). We consider …

Integer‐valued autoregressive (INAR) processes have been introduced to model non‐
negative integer‐valued phenomena that evolve in time. The distribution of an INAR (p) …

There is a need for the development of models that are able to account for discreteness in
data, along with its time series properties and correlation. Our focus falls on INteger-valued …