Robust inference for non-linear regression models from the Tsallis score: Application to coronavirus disease 2019 contagion in Italy

Abstract

We discuss an approach of robust fitting on non-linear regression models, in both frequentist and Bayesian approaches, which can be employed to model and predict the contagion dynamics of the coronavirus disease 2019 (COVID-19) in Italy. The focus is on the analysis of epidemic data using robust dose–response curves, but the functionality is applicable to arbitrary non-linear regression models.