Re-visiting the COVID-19 analysis using the class of high ordered integer-valued time series models with harmonic features.
Healthc Anal (N Y)
; 2: 100086, 2022 Nov.
Article
in En
| MEDLINE
| ID: mdl-37520619
ABSTRACT
The COVID-19 series is obviously one of the most volatile time series with lots of spikes and oscillations. The conventional integer-valued auto-regressive time series models (INAR) may be limited to account for such features in COVID-19 series such as severe over-dispersion, excess of zeros, periodicity, harmonic shapes and oscillations. This paper proposes alternative formulations of the classical INAR process by considering the class of high-ordered INAR models with harmonic innovation distributions. Interestingly, the paper further explores the bivariate extension of these high-ordered INARs. South Africa and Mauritius' COVID-19 series are re-scrutinized under the optic of these new INAR processes. Some simulation experiments are also executed to validate the new models and their estimation procedures.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Language:
En
Journal:
Healthc Anal (N Y)
Year:
2022
Document type:
Article
Affiliation country:
Mauricio