학술논문

Robust inference for nonlinear regression models from the Tsallis score: application to Covid-19 contagion in Italy
Document Type
Working Paper
Source
Subject
Statistics - Applications
Statistics - Methodology
Language
Abstract
We discuss an approach for fitting robust nonlinear regression models, which can be employed to model and predict the contagion dynamics of the 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 nonlinear regression models.
Comment: 15 pages, 6 figures, submitted