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agriReg  

Linear and Nonlinear Regression for Agricultural Data
View on CRAN: Click here


Download and install agriReg package within the R console
Install from CRAN:
install.packages("agriReg")

Install from Github:
library("remotes")
install_github("cran/agriReg")

Install by package version:
library("remotes")
install_version("agriReg", "0.1.0")



Attach the package and use:
library("agriReg")
Maintained by
Sadikul Islam
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-03-31
Latest Update: 2026-03-31
Description:
Fit, compare, and visualise linear and nonlinear regression models tailored to field-trial and dose-response agricultural data. Provides S3 classes for mixed-effects models (via 'lme4'), nonlinear growth curves (logistic, 'Gompertz', asymptotic, linear-plateau, quadratic), and four/five-parameter log-logistic dose-response models (via 'drc'). Includes automated starting-value heuristics, goodness-of-fit statistics, residual diagnostics, and 'ggplot2'-based visualisation. Methods are based on Bates and Watts (1988, ISBN:9780471816430), Ritz and others (2015) <doi:10.1371/journal.pone.0146021>, and Bates and others (2015) <doi:10.18637/jss.v067.i01>.
How to cite:
Sadikul Islam (2026). agriReg: Linear and Nonlinear Regression for Agricultural Data. R package version 0.1.0, https://cran.r-project.org/web/packages/agriReg. Accessed 04 Oct. 2026.
Previous versions and publish date:
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