A new estimation for INAR(1) process with Poisson distribution

Feilong Lu and Dehui Wang ()
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Feilong Lu: University of Science and Technology Liaoning
Dehui Wang: Liaoning University

Computational Statistics, 2022, vol. 37, issue 3, No 8, 1185-1201

Abstract: Abstract The first-order Poisson autoregressive model may be suitable in situations where the time series data are non-negative integer valued. In this article, we propose a new parameter estimator based on empirical likelihood. Our results show that it can lead to efficient estimators by making effective use of auxiliary information. As a by-product, a test statistic is given, testing the randomness of the parameter. The simulation values show that the proposed test statistic works well. We have applied the suggested method to a real count series.

Keywords: Integer-valued time series; Empirical likelihood; Test statistic (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s00180-021-01157-5

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