epifitter: Analysis and Simulation of Plant Disease Progress Curves

Analysis and visualization of plant disease progress curve data. Functions for fitting two-parameter population dynamics models (exponential, monomolecular, logistic and Gompertz) to proportion data for single or multiple epidemics using either linear or no-linear regression. Statistical and visual outputs are provided to aid in model selection. Synthetic curves can be simulated for any of the models given the parameters. See Laurence V. Madden, Gareth Hughes, and Frank van den Bosch (2007) <doi:10.1094/9780890545058> for further information on the methods.

Version: 0.2.0
Depends: R (≥ 3.2)
Imports: deSolve, dplyr, stats, ggplot2, knitr, tidyr, DescTools, minpack.lm, magrittr, tibble
Suggests: rmarkdown, ggridges, cowplot
Published: 2020-11-26
Author: Kaique dos S. Alves ORCID iD [aut, cre], Emerson M. Del Ponte ORCID iD [aut]
Maintainer: Kaique dos S. Alves <kaiquedsalves at gmail.com>
BugReports: https://github.com/AlvesKS/epifitter/issues
License: MIT + file LICENSE
URL: https://github.com/AlvesKS/epifitter
NeedsCompilation: no
Materials: README NEWS
CRAN checks: epifitter results

Downloads:

Reference manual: epifitter.pdf
Vignettes: Fitting and selecting models
Simulating disease progress curves
Package source: epifitter_0.2.0.tar.gz
Windows binaries: r-devel: epifitter_0.2.0.zip, r-release: epifitter_0.2.0.zip, r-oldrel: epifitter_0.2.0.zip
macOS binaries: r-release: epifitter_0.2.0.tgz, r-oldrel: epifitter_0.2.0.tgz
Old sources: epifitter archive

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