epigrowthfit: Nonlinear Mixed Effects Models of Epidemic Growth
Maximum likelihood estimation of nonlinear mixed effects models of
epidemic growth using Template Model Builder ('TMB'). Enables
joint estimation for collections of disease incidence time series,
including time series that describe multiple epidemic waves.
Supports a set of widely used phenomenological models: exponential,
logistic, Richards (generalized logistic), subexponential,
and Gompertz. Provides methods for interrogating model objects
and several auxiliary functions, including one for computing basic
reproduction numbers from fitted values of the initial exponential
growth rate.
Preliminary versions of this software were applied
in Ma et al. (2014) <doi:10.1007/s11538-013-9918-2> and
in Earn et al. (2020) <doi:10.1073/pnas.2004904117>.
Version: |
0.15.3 |
Depends: |
R (≥ 4.3) |
Imports: |
Matrix (≥ 1.6-2), TMB, grDevices, graphics, methods, nlme, stats, tools, utils |
LinkingTo: |
RcppEigen (≥ 0.3.4.0.0), TMB |
Published: |
2024-06-18 |
DOI: |
10.32614/CRAN.package.epigrowthfit |
Author: |
Mikael Jagan
[aut, cre],
Ben Bolker [aut],
Jonathan Dushoff
[ctb],
David Earn [ctb],
Junling Ma [ctb] |
Maintainer: |
Mikael Jagan <jaganmn at mcmaster.ca> |
BugReports: |
https://github.com/davidearn/epigrowthfit/issues |
License: |
GPL-3 |
URL: |
https://github.com/davidearn/epigrowthfit |
NeedsCompilation: |
yes |
Materials: |
NEWS |
In views: |
Epidemiology |
CRAN checks: |
epigrowthfit results |
Documentation:
Downloads:
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