Package: epigrowthfit 0.15.4
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>.
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epigrowthfit_0.15.4.tar.gz
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epigrowthfit.pdf |epigrowthfit.html✨
epigrowthfit/json (API)
NEWS
# Install 'epigrowthfit' in R: |
install.packages('epigrowthfit', repos = c('https://davidearn.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/davidearn/epigrowthfit/issues
- covid19.ontario - COVID-19 in Ontario, Canada
Last updated 3 months agofrom:27f5b89eb5. Checks:OK: 7 ERROR: 2. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 10 2024 |
R-4.5-win-x86_64 | OK | Nov 10 2024 |
R-4.5-linux-x86_64 | OK | Nov 10 2024 |
R-4.4-win-x86_64 | OK | Nov 10 2024 |
R-4.4-mac-x86_64 | ERROR | Nov 10 2024 |
R-4.4-mac-aarch64 | OK | Nov 10 2024 |
R-4.3-win-x86_64 | OK | Nov 10 2024 |
R-4.3-mac-x86_64 | ERROR | Nov 10 2024 |
R-4.3-mac-aarch64 | OK | Nov 10 2024 |
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