Statistics Mauritius, Ministry of Finance, Economic Planning and Development, Port Louis, Mauritius.
Department of Economics and Statistics, University of Mauritius, Moka, Mauritius.
PLoS One. 2022 Feb 8;17(2):e0263515. doi: 10.1371/journal.pone.0263515. eCollection 2022.
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.
本文提出了一些具有零膨胀和泊松混合创新分布的高阶整数自回归时间序列过程 INAR(p)，其中这些分布中的预测函数允许协变量指定，特别是时变协变量。所提出的时间序列结构适合于对毛里求斯的 SARs-CoV-2 序列进行建模，该序列显示出过多的零值，因此具有显著的过分散性和非平稳趋势。此外，INAR 模型允许评估毛里求斯 COVID-19 的可能原因。结果表明，接种疫苗和 COVID-19 严格指数是最能减少当地 COVID-19 病例并最终减少相关死亡病例的因素。此外，基于一些短期预测，具有零膨胀负二项式创新的 INAR(7) 提供了最佳拟合和可靠的均方根误差。不可否认，这些信息将对毛里求斯当局实施全面政策有很大帮助。
