… This work is organized as follows: in Section 2 we define the replicated INAR, RINAR,
processes. In Section 3 we propose several estimation methods from both the classical and the …

… INAR(1) process. Bayesian methodology is used to obtain point predictions as well as credibility
intervals for future values of the process … , from 100 replicates. The simulation results for …

… , INAR (1), with Poisson innovations. We test the null of serial independence, where the INAR
… Zn ) and λ ̂ (for Z n * ) are inserted replicate wise for λ in the response surface equations. …

… Based on these facts, we prefer the CMLE method to obtain the unknown parameters of
INAR(1)DLi-3P process. The conditional loglikelihood function of the INAR(1)DLi-3P process is …

… To cover the caveat of previous studies, in this paper, we are interested in estimating and
forecasting the zero inflated geometric INAR RC ( 1 ) process with random coefficient. …

… integer-valued (ie, N-valued) processes. The model is specified by requiring that the … ends)
capturing individual IP XT+k (produced by a single replication of (14) at given lead-time k ≥ 1…

… of the first-order integer-valued autoregressive process with Poisson innovations, based on
… We also use a test based on our processes for checking if the count time series considered …

… processes, similarly as made by Freeland (Adv Stat Anal 94:217–229, 2010 ). We derive
some joint and conditional basic properties of the proposed process … of our process we apply it …

… (p) process more flexible, using the idea from RrNGINAR(1) … the form like in the RrNGINAR(1)
process, for which we know that … There are 100 replicates, each of size 10000. Both of the …

… PBE2-INAR(p) process is (2.3) P ( X t = x t | X t − 1 = x t − 1 , X … of the ith replication of ξ, and
m is the number of replications. … We use the INAR(1) and INAR(2) models based on the CML …