Modeling and inference for infectious disease dynamics: a likelihood-based approach

DOI10.1214/17-STS636zbMath1407.62397OpenAlexW2785417031WikidataQ54213303 ScholiaQ54213303MaRDI QIDQ667678

Carles Bretó

Publication date: 1 March 2019

Published in: Statistical Science (Search for Journal in Brave)

Full work available at URL: https://projecteuclid.org/euclid.ss/1517562025

zbMATH Keywords

maximum likelihoodcompartment modelenvironmental stochasticitycontinuous-time Markov chainparticle filterLévy-driven stochastic differential equationiterated filtering

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to biology and medical sciences; meta analysis (62P10) Medical epidemiology (92C60)

Related Items (7)

MODELING THE CONTROL OF BACTERIAL DISEASE BY SOCIAL MEDIA ADVERTISEMENTS: EFFECTS OF AWARENESS AND SANITATION ⋮ Bagged Filters for Partially Observed Interacting Systems ⋮ Modeling and inference for infectious disease dynamics: a likelihood-based approach ⋮ Inference of the generalized-growth model via maximum likelihood estimation: a reflection on the impact of overdispersion ⋮ Panel Data Analysis via Mechanistic Models ⋮ Inference in Gaussian state-space models with mixed effects for multiple epidemic dynamics ⋮ Co-jumps and Markov Counting Systems in Random Environments

Uses Software

• pomp

Cites Work

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