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nlraa  

Nonlinear Regression for Agricultural Applications
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("nlraa", "1.9.10")



Attach the package and use:
library("nlraa")
Maintained by
Fernando Miguez
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-01-13
Latest Update: 2025-09-03
Description:
Additional nonlinear regression functions using self-start (SS) algorithms. One of the functions is the Beta growth function proposed by Yin et al. (2003) . There are several other functions with breakpoints (e.g. linear-plateau, plateau-linear, exponential-plateau, plateau-exponential, quadratic-plateau, plateau-quadratic and bilinear), a non-rectangular hyperbola and a bell-shaped curve. Twenty eight (28) new self-start (SS) functions in total. This package also supports the publication 'Nonlinear regression Models and applications in agricultural research' by Archontoulis and Miguez (2015) , a book chapter with similar material and a publication by Oddi et. al. (2019) in Ecology and Evolution . The function 'nlsLMList' uses 'nlsLM' for fitting, but it is otherwise almost identical to 'nlme::nlsList'.In addition, this release of the package provides functions for conducting simulations for 'nlme' and 'gnls' objects as well as bootstrapping. These functions are intended to work with the modeling framework of the 'nlme' package. It also provides four vignettes with extended examples.
How to cite:
Fernando Miguez (2020). nlraa: Nonlinear Regression for Agricultural Applications. R package version 1.9.10, https://cran.r-project.org/web/packages/nlraa. Accessed 07 Oct. 2026.
Previous versions and publish date:
(2026-07-09 06:25), 0.53 (2020-01-13 17:20), 0.65 (2020-04-25 03:50), 0.73 (2020-06-12 16:30), 0.76 (2020-11-09 14:40), 0.83 (2021-01-05 14:50), 0.89 (2021-04-22 02:10), 0.98 (2021-08-18 23:50), 1.1 (2022-02-09 00:50), 1.2 (2022-02-14 16:10), 1.5 (2022-08-17 09:00), 1.9.3 (2023-06-15 02:10), 1.9.7 (2023-12-19 06:50)
Other packages that cited nlraa R package
View nlraa citation profile
Other R packages that nlraa depends, imports, suggests or enhances
Complete documentation for nlraa
Functions, R codes and Examples using the nlraa R package
Some associated functions: IA_tab . IC_tab . Lob.bt.pe . R2M . SSagauss . SSbell . SSbeta5 . SSbg4rp . SSbgf . SSbgf4 . SSbgrp . SSblin . SScard3 . SSdlf . SSexpf . SSexpfp . SSexplin . SSharm . SShill . SSlinp . SSlogis5 . SSmoh . SSnrh . SSpexpf . SSplin . SSpquad . SSpquad3 . SSprofd . SSquadp . SSquadp3 . SSquadp3xs . SSratio . SSricker . SSscard3 . SSsharp . SStemp . SStrlin . barley . boot_lm . boot_lme . boot_nlme . boot_nls . fm1.P.at.x.0.4 . fm1.P.bt.ft . fm1.P.bt . fm2.Lob.bt . fmm1.bt . lfmc . maizeleafext . nlraa.env . nlsLMList.formula . nlsLMList . predict2_nls . predict_gam . predict_nlme . predict_nls . print_boot . simulate_gam . simulate_gls . simulate_gnls . simulate_lm . simulate_lme . simulate_nlme . simulate_nlme_one . simulate_nls . sm . summary_simulate . swpg . var_cov . 
Some associated R codes: IA_tab.R . SSagauss.R . SSbell.R . SSbeta5.R . SSbg4rp.R . SSbgf.R . SSbgf4.R . SSbgrp.R . SSblin.R . SSdlf.R . SSexpf.R . SSexpfp.R . SSexplin.R . SSharm.R . SShill.R . SSlinp.R . SSlogis5.R . SSmoh.R . SSnrh.R . SSpexpf.R . SSplin.R . SSpquad.R . SSpquad3.R . SSprofd.R . SSquadp.R . SSquadp3.R . SSquadp3xs.R . SSratio.R . SSricker.R . SSscard3.R . SSsharp.R . SStemp.R . SStrlin.R . boot_lm.R . boot_lme.R . boot_nlme.R . boot_nls.R . data-doc.R . nlsLMList.R . predict_nlme.R . predict_nls.R . print.boot.R . simulate_gam.R . simulate_gls.R . simulate_gnls.R . simulate_lm.R . simulate_lme.R . simulate_nlme.R . simulate_nlme_one.R . simulate_nls.R . summary_simulate.R . var_cov.R .  Full nlraa package functions and examples
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