On Computer-Intensive Simulation and ...
Type de document :
Article dans une revue scientifique: Article original
DOI :
Titre :
On Computer-Intensive Simulation and Estimation Methods for Rare Event Analysis in Epidemic Models
Auteur(s) :
Clémençon, Stéphan [Auteur correspondant]
Département Images, Données, Signal [IDS]
Laboratoire Traitement et Communication de l'Information [LTCI]
Cousien, Anthony [Auteur correspondant]
Infection, Anti-microbiens, Modélisation, Evolution [IAME (UMR_S_1137 / U1137)]
Dávila Felipe, Miraine [Auteur correspondant]
Laboratoire de Probabilités et Modèles Aléatoires [LPMA]
Tran, Chi [Auteur correspondant]
Laboratoire Paul Painlevé - UMR 8524 [LPP]
Département Images, Données, Signal [IDS]
Laboratoire Traitement et Communication de l'Information [LTCI]
Cousien, Anthony [Auteur correspondant]
Infection, Anti-microbiens, Modélisation, Evolution [IAME (UMR_S_1137 / U1137)]
Dávila Felipe, Miraine [Auteur correspondant]
Laboratoire de Probabilités et Modèles Aléatoires [LPMA]
Tran, Chi [Auteur correspondant]

Laboratoire Paul Painlevé - UMR 8524 [LPP]
Titre de la revue :
Statistics in Medicine
Pagination :
3696-3713
Éditeur :
Wiley-Blackwell
Date de publication :
2015
ISSN :
0277-6715
Mot(s)-clé(s) en anglais :
Stochastic epidemic model
interacting branching particle system
importance sampling
genetic models
multilevel splitting
rare event analysis
Monte-Carlo simulation
interacting branching particle system
importance sampling
genetic models
multilevel splitting
rare event analysis
Monte-Carlo simulation
Discipline(s) HAL :
Statistiques [stat]/Applications [stat.AP]
Mathématiques [math]/Statistiques [math.ST]
Statistiques [stat]/Théorie [stat.TH]
Sciences du Vivant [q-bio]/Santé publique et épidémiologie
Mathématiques [math]/Probabilités [math.PR]
Statistiques [stat]/Machine Learning [stat.ML]
Mathématiques [math]/Statistiques [math.ST]
Statistiques [stat]/Théorie [stat.TH]
Sciences du Vivant [q-bio]/Santé publique et épidémiologie
Mathématiques [math]/Probabilités [math.PR]
Statistiques [stat]/Machine Learning [stat.ML]
Résumé en anglais : [en]
This article focuses, in the context of epidemic models, on rare events that may possibly correspond to crisis situations from the perspective of Public Health. In general, no close analytic form for their occurrence ...
Lire la suite >This article focuses, in the context of epidemic models, on rare events that may possibly correspond to crisis situations from the perspective of Public Health. In general, no close analytic form for their occurrence probabilities is available and crude Monte-Carlo procedures fail. We show how recent intensive computer simulation techniques, such as interacting branching particle methods, can be used for estimation purposes, as well as for generating model paths that correspond to realizations of such events. Applications of these simulation-based methods to several epidemic models are also considered and discussed thoroughly.Lire moins >
Lire la suite >This article focuses, in the context of epidemic models, on rare events that may possibly correspond to crisis situations from the perspective of Public Health. In general, no close analytic form for their occurrence probabilities is available and crude Monte-Carlo procedures fail. We show how recent intensive computer simulation techniques, such as interacting branching particle methods, can be used for estimation purposes, as well as for generating model paths that correspond to realizations of such events. Applications of these simulation-based methods to several epidemic models are also considered and discussed thoroughly.Lire moins >
Langue :
Anglais
Comité de lecture :
Oui
Audience :
Internationale
Vulgarisation :
Non
Collections :
Source :
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