Package: epigrowthfit 0.15.4

Mikael Jagan

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>.

Authors:Mikael Jagan [aut, cre], Ben Bolker [aut], Jonathan Dushoff [ctb], David Earn [ctb], Junling Ma [ctb]

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epigrowthfit.pdf |epigrowthfit.html✨
epigrowthfit/json (API)
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Bug tracker:https://github.com/davidearn/epigrowthfit/issues

On CRAN:

24 exports 9 stars 2.31 score 6 dependencies 45 scripts 158 downloads

Last updated 1 months agofrom:27f5b89eb5. Checks:OK: 9. Indexed: yes.

Exports:cov2thetadgiegfegf_controlegf_control_plotegf_has_convergedegf_has_randomegf_modelegf_optimizeregf_parallelegf_topfinalsizefixefInverseWishartLKJNormalpgiqgiR0ranefrgitheta2covtimescaleWishart

Dependencies:latticeMatrixnlmeRcppRcppEigenTMB