Poisson-Lindley INAR(1) Processes: Some Estimation and Forecasting Methods

This paper focuses on different methods of estimation and forecasting in first-order integer-valued autoregressive processes with Poisson-Lindley (PLINAR(1)) marginal distribution. For this purpose, the parameters of the model are estimated using Whittle, maximum empirical likelihood and sieve bootstrap methods. Moreover, Bayesian and sieve bootstrap forecasting methods are proposed and predicted value for h-step ahead of the series is obtained. Some simulations and a real data analysis are applied to compare the presented estimations and the prediction methods.