Package: epifitter 0.3.0

Kaique dos S. Alves

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.

Authors:Kaique dos S. Alves [aut, cre], Emerson M. Del Ponte [aut]

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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

Datasets:

PowderyMildew - Dataset powdery mildew disease progress curves

On CRAN:

17 exports 5 stars 1.11 score 71 dependencies 48 scripts 300 downloads

Last updated 3 years agofrom:00af96a8a8. Checks:OK: 1 NOTE: 6. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Sep 17 2024
R-4.5-win	NOTE	Sep 17 2024
R-4.5-linux	NOTE	Sep 17 2024
R-4.4-win	NOTE	Sep 17 2024
R-4.4-mac	NOTE	Sep 17 2024
R-4.3-win	NOTE	Sep 17 2024
R-4.3-mac	NOTE	Sep 17 2024

Exports:AUDPC AUDPS expo_fun fit_lin fit_multi fit_nlin fit_nlin2 gompi_fun logi_fun mono_fun plot_fit print.fit_lin print.fit_nlin2 sim_exponential sim_gompertz sim_logistic sim_monomolecular

Dependencies:askpass boot cellranger class cli colorspace cpp11 crayon curl data.table DescTools deSolve dplyr e1071 evaluate Exact expm fansi farver generics ggplot2 gld glue gtable highr hms httr isoband jsonlite knitr labeling lattice lifecycle lmom magrittr MASS Matrix mgcv mime minpack.lm munsell mvtnorm nlme openssl pillar pkgconfig prettyunits progress proxy purrr R6 RColorBrewer Rcpp readxl rematch rlang rootSolve rstudioapi scales stringi stringr sys tibble tidyr tidyselect utf8 vctrs viridisLite withr xfun yaml

Fitting and selecting models

Kaique S Alves

Rendered fromfitting.Rmdusingknitr::rmarkdownon Sep 17 2024.

Last update: 2021-06-01
Started: 2020-09-02

Simulating disease progress curves

Kaique S Alves

Rendered fromsimulation.Rmdusingknitr::rmarkdownon Sep 17 2024.

Last update: 2021-06-01
Started: 2020-09-02

Help page	Topics
Area under disease progress curve	AUDPC
Area under disease progress stairs	AUDPS
Function for Exponential model	expo_fun
Fits epidemic models using data linearization	fit_lin
Estimate model parameters for multiple disease progress curves	fit_multi
Fits epidemic models using nonlinear aproach	fit_nlin
Fits epidemic models using nonlinear aproach. This function also estimates the maximum disease intensity parameter K	fit_nlin2
Function for Gompertz model	gompi_fun
Function for logistic model	logi_fun
Function for Monomolecular model	mono_fun
Creates a plot panel for the fitted models	plot_fit
Dataset powdery mildew disease progress curves	PowderyMildew
Print 'fit_lin()' or 'fit_nlin()' outputs	print.fit_lin
Print 'fit_nlin2()' outputs	print.fit_nlin2
Simulate an epidemic using the Exponential model	sim_exponential
Simulate an epidemic using the Gompertz model	sim_gompertz
Simulate an epidemic using the logistic model	sim_logistic
Simulate an epidemic using the Monomolecular model	sim_monomolecular

Package: epifitter 0.3.0

epifitter: Analysis and Simulation of Plant Disease Progress Curves

Fitting and selecting models

Simulating disease progress curves

Citation

Development and contributors

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)