Package: epifitter 1.0.0


Kaique dos S. Alves
epifitter: Analysis and Simulation of Plant Disease Progress Curves
Tools for analysis, visualization, and simulation of plant disease progress curves. Includes functions to calculate area-under-the-curve summaries, fit and compare exponential, monomolecular, logistic, and Gompertz models using linear or nonlinear regression, work with single or multiple epidemics, and produce 'ggplot2'-based visualizations. Also includes an experimental powdery mildew dataset for reproducible teaching and research workflows. See Madden, Hughes, and van den Bosch (2007) <doi:10.1094/9780890545058> for background on the epidemiological methods.
Authors:
epifitter_1.0.0.tar.gz
epifitter_1.0.0.zip(r-4.7)epifitter_1.0.0.zip(r-4.6)epifitter_1.0.0.zip(r-4.5)
epifitter_1.0.0.tgz(r-4.6-any)epifitter_1.0.0.tgz(r-4.5-any)
epifitter_1.0.0.tar.gz(r-4.7-any)epifitter_1.0.0.tar.gz(r-4.6-any)
epifitter_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
epifitter/json (API)
NEWS
| # Install 'epifitter' in R: |
| install.packages('epifitter', repos = c('https://alvesks.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/alvesks/epifitter/issues
Pkgdown/docs site:https://alvesks.github.io
- PowderyMildew - Powdery mildew disease progress curves in organic tomato
Last updated from:1791d02dfc. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 162 | ||
| source / vignettes | OK | 202 | ||
| linux-release-x86_64 | OK | 141 | ||
| macos-release-arm64 | OK | 128 | ||
| macos-oldrel-arm64 | OK | 202 | ||
| windows-devel | OK | 94 | ||
| windows-release | OK | 133 | ||
| windows-oldrel | OK | 99 | ||
| wasm-release | OK | 122 |
Exports:AUDPCAUDPC_2_pointsAUDPSexpo_funfit_linfit_multifit_nlinfit_nlin2gompi_funlogi_funmono_funplot_fitsim_exponentialsim_gompertzsim_logisticsim_monomolecular
Dependencies:askpassbitbit64bootcellrangerclassclicliprcowplotcpp11crayoncurldata.tableDescToolsdeSolvedplyre1071Exactexpmfarverforcatsfsgenericsggplot2gldgluegtablehavenhmshttrisobandjsonlitelabelinglatticelifecyclelmommagrittrMASSMatrixmimeminpack.lmmvtnormopensslpillarpkgconfigprettyunitsprogressproxypurrrR6RColorBrewerRcppreadrreadxlrematchrlangrootSolverstudioapiS7scalesstringistringrsystibbletidyrtidyselecttzdbutf8vctrsviridisLitevroomwithr
Area-under-the-curve summaries
Rendered fromarea-under-curve.Rmdusingknitr::rmarkdownon May 12 2026.Last update: 2026-04-11
Started: 2026-04-11
Getting started with epifitter
Rendered fromgetting-started.Rmdusingknitr::rmarkdownon May 12 2026.Last update: 2026-04-11
Started: 2026-04-11
Model fitting workflows
Rendered frommodel-fitting.Rmdusingknitr::rmarkdownon May 12 2026.Last update: 2026-04-11
Started: 2026-04-11
Simulation workflows
Rendered fromsimulation-workflows.Rmdusingknitr::rmarkdownon May 12 2026.Last update: 2026-04-11
Started: 2026-04-11
Working with the PowderyMildew dataset
Rendered frompowdery-mildew-data.Rmdusingknitr::rmarkdownon May 12 2026.Last update: 2026-04-11
Started: 2026-04-11
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Area under the disease progress curve | AUDPC |
| Estimate AUDPC from two observations | AUDPC_2_points |
| Area under the disease progress stairs | AUDPS |
| Exponential model differential equation | expo_fun |
| Fit epidemic models using linearization | fit_lin |
| Fit models to multiple disease progress curves | fit_multi |
| Fit epidemic models using nonlinear regression | fit_nlin |
| Fit epidemic models and estimate the asymptote | fit_nlin2 |
| Gompertz model differential equation | gompi_fun |
| Logistic model differential equation | logi_fun |
| Monomolecular model differential equation | mono_fun |
| Plot fitted epidemic models | plot_fit |
| Powdery mildew disease progress curves in organic tomato | PowderyMildew |
| Print fitted model summaries | print.fit_lin |
| Print fitted model summaries with asymptote estimates | print.fit_nlin2 |
| Simulate an exponential disease progress curve | sim_exponential |
| Simulate a Gompertz disease progress curve | sim_gompertz |
| Simulate a logistic disease progress curve | sim_logistic |
| Simulate a monomolecular disease progress curve | sim_monomolecular |