In:
PLOS ONE, Public Library of Science (PLoS), Vol. 17, No. 2 ( 2022-2-8), p. e0263515-
Abstract:
This paper proposes some high-ordered integer-valued auto-regressive time series process of order p (INAR( p )) with Zero-Inflated and Poisson-mixtures innovation distributions, wherein the predictor functions in these mentioned distributions allow for covariate specification, in particular, time-dependent covariates. The proposed time series structures are tested suitable to model the SARs-CoV-2 series in Mauritius which demonstrates excess zeros and hence significant over-dispersion with non-stationary trend. In addition, the INAR models allow the assessment of possible causes of COVID-19 in Mauritius. The results illustrate that the event of Vaccination and COVID-19 Stringency index are the most influential factors that can reduce the locally acquired COVID-19 cases and ultimately, the associated death cases. Moreover, the INAR(7) with Zero-inflated Negative Binomial innovations provides the best fitting and reliable Root Mean Square Errors, based on some short term forecasts. Undeniably, these information will hugely be useful to Mauritian authorities for implementation of comprehensive policies.
Type of Medium:
Online Resource
ISSN:
1932-6203
DOI:
10.1371/journal.pone.0263515
DOI:
10.1371/journal.pone.0263515.g001
DOI:
10.1371/journal.pone.0263515.g002
DOI:
10.1371/journal.pone.0263515.g003
DOI:
10.1371/journal.pone.0263515.g004
DOI:
10.1371/journal.pone.0263515.g005
DOI:
10.1371/journal.pone.0263515.g006
DOI:
10.1371/journal.pone.0263515.t001
DOI:
10.1371/journal.pone.0263515.t002
DOI:
10.1371/journal.pone.0263515.t003
DOI:
10.1371/journal.pone.0263515.t004
DOI:
10.1371/journal.pone.0263515.s001
Language:
English
Publisher:
Public Library of Science (PLoS)
Publication Date:
2022
detail.hit.zdb_id:
2267670-3
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