Regression Analysis Linear and Nonlinear for Agriculture

Linear and nonlinear regression analysis common in agricultural science articles (Archontoulis & Miguez (2015). ). The package includes polynomial, exponential, gaussian, logistic, logarithmic, segmented, non-parametric models, among others. 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.

AgroReg

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Package: AgroReg

Type: Package

Title: Regression Analysis Linear and Nonlinear for Agriculture

Version: 1.2.3

Date: 2022-05-04

Authors: Gabriel Danilo Shimizu & Leandro Simoes Azeredo Goncalves

Maintainer: Gabriel Danilo Shimizu [email protected]

Description: Linear and nonlinear regression analysis common in agricultural science articles (Archontoulis & Miguez (2015). doi:10.2134/agronj2012.0506). The package includes polynomial, exponential, gaussian, logistic, logarithmic, segmented, non-parametric models, among others. 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.

License: GPL (>= 2)

Imports: drc, ggplot2, boot, minpack.lm, dplyr, rcompanion, broom, egg

Depends: R (>= 3.6)

Encoding: UTF-8

LazyData: true

RoxygenNote: 7.1.2

Installation

# Install release version from CRAN
install.packages("AgroReg")

# Install development version from GitHub
devtools::install_github("https://github.com/AgronomiaR/AgroReg.git")