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Higher-Order INAR Model Based on a Flexible Innovation and Application to COVID-19 and Gold Particles Data.

Authors :
Almuhayfith, Fatimah E.
Krishna, Anuresha
Maya, Radhakumari
Irshad, Muhammad Rasheed
Bakouch, Hassan S.
Almulhim, Munirah
Source :
Axioms (2075-1680); Jan2024, Vol. 13 Issue 1, p32, 16p
Publication Year :
2024

Abstract

INAR models have the great advantage of being able to capture the conditional distribution of a count time series based on their past observations, thus allowing it to be tailored to meet the unique characteristics of count data. This paper reviews the two-parameter Poisson extended exponential (PEE) distribution and its corresponding INAR(1) process. Then the INAR of order p (INAR(p)) model that incorporates PEE innovations is proposed, its statistical properties are presented, and its parameters are estimated using conditional least squares and conditional maximum likelihood estimation methods. Two practical data sets are analyzed and compared with competing INAR models in an effort to gauge the performance of the proposed model. It is found that the proposed model performs better than the competitors. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20751680
Volume :
13
Issue :
1
Database :
Complementary Index
Journal :
Axioms (2075-1680)
Publication Type :
Academic Journal
Accession number :
175058654
Full Text :
https://doi.org/10.3390/axioms13010032