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

EasyChair Preprint 7791

Abstract

In this study, we focus on the spread of COVID–19 on besides of vaccination of this disease. Total infected cases of COVID–19 have considered and model it by a light/heavy tailed auto–regressive model with innovations belong on the flexible class of the two-piece scale mixtures of normal (TP–SMN) 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 COVID–19 in the U.S. has considered and vaccinated numbers of COVID–19 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

@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}}