Computational Statistics

, Volume 34, Issue 4, pp 1815–1848 | Cite as

Model-based INAR bootstrap for forecasting INAR(p) models

  • Luisa BisagliaEmail author
  • Margherita Gerolimetto
Original paper


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 when estimating the thinning parameters in INAR(p) models; we state the superiority of model-based INAR bootstrap approaches on block bootstrap in terms of low bias and Mean Square Error. Then we adopt the model-based bootstrap methods to obtain coherent predictions and confidence intervals in order to avoid difficulty in deriving the distributional properties. Finally, we present an empirical application.


INAR(p) models Estimation Forecast Bootstrap 



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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of StatisticsUniversity of PadovaPaduaItaly
  2. 2.Department of EconomicsCa’ Foscari University VeniceVeniceItaly

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