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Time Indexed Covariate Analysis of the Administered Vaccine Doses on Covid-19 Spread

EasyChair Preprint 7791

19 pagesDate: April 18, 2022

Abstract

In this study, we focus on the spread of COVID19 on besides of vaccination of this disease. Total infected cases of COVID19 have considered and model it by a light/heavy tailed autoregressive model with innovations belong on the flexible class of the two-piece scale mixtures of normal (TPSMN) family. Also considering the covariate variables which are indexed by time are considered in the model to more accuracy of modeling. An EM type algorithm has considered for finding the maximum likelihood estimations of the model parameters. Modelling and prediction of infected numbers of COVID19 in the U.S. has considered and vaccinated numbers of COVID19 is considered as auxiliary (covariate) in the model.

Keyphrases: Auto–regressive model with covariate, COVID–19, ECME–algorithm, Infected numbers of COVID–19, ML estimates, Two-piece scale mixtures of normal family, Vaccinated numbers of COVID–19, vaccinated cases

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@booklet{EasyChair:7791,
  author    = {Mohsen Maleki and Mohammad Reza Mahmoudi and Hamid Bidram and Amir Mosavi},
  title     = {Time Indexed Covariate Analysis of the Administered Vaccine Doses on Covid-19 Spread},
  howpublished = {EasyChair Preprint 7791},
  year      = {EasyChair, 2022}}
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