Selected article for: "bayesian approach and frequentist approach"

Author: Girardi, Paolo; Greco, Luca; Mameli, Valentina; Musio, Monica; Racugno, Walter; Ruli, Erlis; Ventura, Laura
Title: Robust inference for nonlinear regression models from the Tsallis score: application to COVID‐19 contagion in Italy
  • Cord-id: bmppif8g
  • Document date: 2020_8_12
  • ID: bmppif8g
    Snippet: We discuss an approach of robust fitting on nonlinear regression models, both in a frequentist and a Bayesian approach, which can be employed to model and predict the contagion dynamics of 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.
    Document: We discuss an approach of robust fitting on nonlinear regression models, both in a frequentist and a Bayesian approach, which can be employed to model and predict the contagion dynamics of 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.

    Search related documents:
    Co phrase search for related documents
    • Try single phrases listed below for: 1