Covid19 Reproduction Number: Credibility Intervals by Blockwise Proximal Monte Carlo Samplers

Author:

Fort Gersende1ORCID,Pascal Barbara2ORCID,Abry Patrice3ORCID,Pustelnik Nelly3ORCID

Affiliation:

1. Institut de Mathématiques de Toulouse, CNRS, Toulouse, France

2. Nantes Université, École Centrale Nantes, CNRS, LS2N, UMR 6004, Nantes, France

3. ENS de Lyon, Laboratoire de Physique, CNRS, Lyon, France

Funder

Fondation Simone et Cino Del Duca

Institut de France

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Signal Processing

Reference63 articles.

1. Discussion: Markov Chains for Exploring Posterior Distributions

2. The impact of a nation-wide lockdown on COVID-19 transmissibility in Italy;guzzetta,2020

3. Epidemiological characteristics of COVID-19 cases in Italy and estimates of the reproductive numbers one month into the epidemic;riccardo;Euro Surveill,2020

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1. Pandemic Intensity Estimation from Stochastic Approximation-Based Algorithms;2023 IEEE 9th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP);2023-12-10

2. Proximal-Langevin Samplers for Nonsmooth Composite Posteriors: Application to the Estimation of Covid19 Reproduction Number;2023 31st European Signal Processing Conference (EUSIPCO);2023-09-04

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