A new generalized binomial thinning-based INAR(1) process with Poisson–Lindley innovations

This paper considers a new parameterization of the generalized binomial thinning operator that is to be incorporated in a simple ordered integer-valued autoregressive process (INAR(1)) with the Poisson–Lindley innovations. The statistical properties of the resulting INAR(1) process are explored along with the estimation procedures. Monte Carlo simulation experiments are executed to assess the consistency of the estimates under the new INAR(1) process. Finally, the importance of the proposed INAR(1) model is confirmed through the analysis of a real data set.

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Publication Details

Journal
Statistical Theory and Related Fields
Published
2025-09-25
DOI
https://doi.org/10.1080/24754269.2025.2557723
Primary Topic
Optimization and Packing Problems
Type
article
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article

A new generalized binomial thinning-based INAR(1) process with Poisson–Lindley innovations

Veena D’cruz, Naushad Mamode Khan, M. R. Irshad, Emad‐Eldin A. A. Aly et al.
Statistical Theory and Related Fields
Optimization and Packing Problems
article

A new generalized binomial thinning-based INAR(1) process with Poisson–Lindley innovations

Veena D’cruz, Naushad Mamode Khan, M. R. Irshad, Emad‐Eldin A. A. Aly, Radhakumari Maya
article en

Abstract

This paper considers a new parameterization of the generalized binomial thinning operator that is to be incorporated in a simple ordered integer-valued autoregressive process (INAR(1)) with the Poisson–Lindley innovations. The statistical properties of the resulting INAR(1) process are explored along with the estimation procedures. Monte Carlo simulation experiments are executed to assess the consistency of the estimates under the new INAR(1) process. Finally, the importance of the proposed INAR(1) model is confirmed through the analysis of a real data set.

Statistical Theory and Related FieldsVol. 9(4)
Cochin University of Science and Technology (IN), Kuwait University (KW), University of Mauritius (MU)
Openalex Percentile: Top 63%
Optimization and Packing Problems
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