R: Linear and Nonlinear Regression for Agricultural Data

# Linear and Nonlinear Regression for Agricultural Data

## Documentation for package ‘agriReg’ version 0.1.0

- DESCRIPTION file.
- User guides, package vignettes and other documentation.

## Help Pages

agriReg-package | agriReg: Linear and Nonlinear Regression for Agricultural Data
agriReg | agriReg: Linear and Nonlinear Regression for Agricultural Data
clean_agri_data | Clean and validate agricultural field-trial data
compare_models | Compare multiple agriReg models side by side
ed_estimates | Compute effective dose (ED) estimates from a dose-response model
fit_dose_response | Fit a log-logistic or Weibull dose-response model
fit_linear | Fit a linear or mixed-effects model for agricultural trials
fit_nonlinear | Fit a nonlinear growth or response curve to agricultural data
fit_polynomial | Fit a sequence of polynomial linear models and pick the best
gof_stats | Compute goodness-of-fit statistics for a model
herbicide_trial | Simulated herbicide dose-response dataset
load_example_data | Load a bundled agriReg example dataset
maize_growth | Simulated maize growth time-series
model_summary | Comprehensive model summary with fit statistics
optimum_dose | Find the optimal x value (e.g. economic optimum dose)
outlier_flag | Flag outliers using multiple methods
plot.agriDRC | Plot a fitted dose-response curve
plot.agriLM | Plot diagnostics for an agriLM model
plot.agriNLS | Plot a fitted nonlinear curve over observed data
plot_fit | A convenience wrapper for ggplot2 visualisation of model fit
residual_check | Residual diagnostic plot panel
wheat_trial | Simulated wheat nitrogen-response trial
yield_normalize | Normalise yield values within groups