Linear and Nonlinear Regression for Agricultural Data R package agriReg version 0.1.0 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>. Software Depends: R (>= 4.1.0) Imports: lme4 (>= 1.1-35), drc (>= 3.0-1), ggplot2 (>= 3.4.0), patchwork (>= 1.1.0), stats, utils Suggests: broom (>= 1.0.0), broom.mixed (>= 0.2.9), emmeans (>= 1.8.0), nlme (>= 3.1-0), methods, testthat (>= 3.0.0), knitr, rmarkdown, lmerTest, car, multcomp Sadikul Islam <sadikul.islamiasri@gmail.com> Comprehensive R Archive Network (CRAN) Sadikul Islam [aut, cre] (ORCID: <https://orcid.org/0000-0003-2924-7122>) MIT + file LICENSE (https://CRAN.R-project.org/package=agriReg/LICENSE) 2026-03-31 application/tgz https://CRAN.R-project.org/package=agriReg doi:10.32614/CRAN.package.agriReg en-US