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On computer‐intensive simulation and estimation methods for rare‐event analysis in epidemic models
Author(s) -
Clémençon Stéphan,
Cousien Anthony,
Felipe Miraine Dávila,
Tran Viet Chi
Publication year - 2015
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.6596
Subject(s) - computer science , monte carlo method , context (archaeology) , estimation , rare events , event (particle physics) , perspective (graphical) , econometrics , data mining , operations research , statistics , artificial intelligence , mathematics , geography , physics , management , archaeology , quantum mechanics , economics
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 fitted from real datasets are also considered and discussed thoroughly. Copyright © 2015 John Wiley & Sons, Ltd.