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Improving epidemic size prediction through stable reconstruction of disease parameters by reduced iteratively regularized Gauss–Newton algorithm.

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Bibliographic Details
Title: Improving epidemic size prediction through stable reconstruction of disease parameters by reduced iteratively regularized Gauss–Newton algorithm.
Authors: Smirnova, Alexandra1 asmirnova@gsu.edu, Chowell-Puente, Gerardo2 gchowell@gsu.edu, deCamp, Linda1 ldecamp1@student.gsu.edu, Moghadas, Seyed3 moghadas@yorku.ca, Jameson Sheppard, Michael1 msheppard6@student.gsu.edu
Source: Journal of Inverse & Ill-Posed Problems. Oct2017, Vol. 25 Issue 5, p653-667. 15p.
Database: Mathematics Source
Description
ISSN:09280219
DOI:10.1515/jiip-2016-0053