Regression Analysis Linear and Nonlinear for Agriculture

Linear and nonlinear regression analysis common in agricultural science papers (Archontoulis & Miguez (2015). ). The package includes linear, quadratic, cubic, inverse quadratic, exponential, negative exponential, biexponential, Gaussian, three- or four-parameter logistic, four- or five-parameter Brain-Cousens logistic, four- or five-parameter Cedergreen-Ritz-Streibig logistic models. five parameters, Gompertz logistic, Michaelis-Menten, logarithmic, linear-linear segmented, linear-plate segmented, quadratic-plate segmented, nonparametric loess. The functions return the model coefficients and their respective p values, coefficient of determination, root mean square error, AIC, BIC, as well as graphs with the equations automatically.


Reference manual

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1.1.0 by Gabriel Danilo Shimizu, a month ago

Browse source code at

Authors: Gabriel Danilo Shimizu [aut, cre] , Leandro Simoes Azeredo Goncalves [aut, ctb]

Documentation:   PDF Manual  

GPL (>= 2) license

Imports drc, ggplot2, car, crayon, boot, minpack.lm, dplyr, rcompanion, broom

See at CRAN