Package: nlraa 1.9.11

Fernando Miguez

nlraa: Nonlinear Regression for Agricultural Applications

Additional nonlinear regression functions using self-start (SS) algorithms. One of the functions is the Beta growth function proposed by Yin et al. (2003) <doi:10.1093/aob/mcg029>. 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) <doi:10.2134/agronj2012.0506>, a book chapter with similar material <doi:10.2134/appliedstatistics.2016.0003.c15> and a publication by Oddi et. al. (2019) in Ecology and Evolution <doi:10.1002/ece3.5543>. 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.

Authors:Fernando Miguez [aut, cre], Caio dos Santos [ctb], José Pinheiro [ctb, cph], Douglas Bates [ctb, cph], R-core [ctb, cph]

nlraa_1.9.11.tar.gz
nlraa_1.9.11.zip(r-4.7)nlraa_1.9.11.zip(r-4.6)nlraa_1.9.11.zip(r-4.5)
nlraa_1.9.11.tgz(r-4.6-any)nlraa_1.9.11.tgz(r-4.5-any)
nlraa_1.9.11.tar.gz(r-4.7-any)nlraa_1.9.11.tar.gz(r-4.6-any)
nlraa_1.9.11.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
nlraa/json (API)

# Install 'nlraa' in R:
install.packages('nlraa', repos = c('https://femiguez.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/femiguez/nlraa/issues

Datasets:
  • barley - Barley response to nitrogen fertilizer
  • fm1.P.at.x.0.4 - Object for confidence bands vignette fm1.P.at.x.0.4
  • fm1.P.bt - Object for confidence bands vignette fm1.P.bt
  • fm1.P.bt.ft - Object for confidence bands vignette fm1.P.bt.ft
  • fm2.Lob.bt - Object for confidence bands vignette fm2.Lob.bt
  • fmm1.bt - Object for confidence bands vignette fmm1.bt
  • lfmc - Live fuel moisture content
  • Lob.bt.pe - Object for confidence bands vignette Lob.bt.pe
  • maizeleafext - Maize leaf extension rate as a response to temperature
  • sm - Sorghum and Maize growth in Greece
  • swpg - Water limitations for Soybean growth

On CRAN:

Conda:

agriculturalecologynonlinear-mixed-modelsnonlinear-regression

8.32 score 25 stars 2 packages 140 scripts 936 downloads 2 mentions 106 exports 11 dependencies

Last updated from:d6afbf815a. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK192
source / vignettesOK296
linux-release-x86_64OK186
macos-release-arm64OK129
macos-oldrel-arm64OK137
windows-develOK207
windows-releaseOK143
windows-oldrelOK151
wasm-releaseOK138

Exports:agaussbellbeta5bg4rpbgfbgf2bgf4bgrpblinboot_glsboot_gnlsboot_lmboot_lmeboot_nlmeboot_nlscard3confidence_intervalsdlfexpfexpfpexplingmicmenharm1hill1hill2hill3IA_tabIC_tablinplogis5mohnlraa.envnlsLMListnrhpexpfplinpquadpquad3predict_gampredict_glspredict_gnlspredict_lmepredict_nlmepredict_nlspredict2_gampredict2_nlsprofdquadpquadp3quadp3xsquadpqR2Mratiorickerscard3sharpsimulate_gamsimulate_glssimulate_gnlssimulate_lmsimulate_lmesimulate_nlmesimulate_nlssphericalSSagaussSSbellSSbeta5SSbg4rpSSbgfSSbgf4SSbgrpSSblinSScard3SSdlfSSexpfSSexpfpSSexplinSSgmicmenSSharm1SShill1SShill2SShill3SSlinpSSlogis5SSmohSSnrhSSpexpfSSplinSSpquadSSpquad3SSprofdSSquadpSSquadp3SSquadp3xsSSquadpqSSratioSSrickerSSscard3SSsharpSSsphericalSStemp3SStrlinsummary_simulatetemp3trlinvar_cov

Dependencies:bootevaluatehighrknitrlatticeMASSMatrixmgcvnlmexfunyaml

Confidence and Prediction Bands Methods for Nonlinear Models

Rendered fromConfidence-Bands.Rmdusingknitr::rmarkdownon May 20 2026.

Last update: 2023-06-09
Started: 2021-05-13

nlraa: An R package for Nonlinear Regression Applications in Agricultural Research

Rendered fromnlraa.Rmdusingknitr::rmarkdownon May 20 2026.

Last update: 2025-08-11
Started: 2019-08-12

nlraa: Models and Functions for Mixed Models

Rendered fromModels-and-Functions.Rmdusingknitr::rmarkdownon May 20 2026.

Last update: 2020-11-09
Started: 2020-06-12

Nonlinear Regression (Archontoulis and Miguez) paper

Rendered fromnlraa-AgronJ-paper.Rmdusingknitr::rmarkdownon May 20 2026.

Last update: 2020-11-09
Started: 2019-08-12

Prediction, Bootstrap and Simulation for Nonlinear Models

Rendered fromBootstrapping.Rmdusingknitr::rmarkdownon May 20 2026.

Last update: 2025-08-11
Started: 2020-04-16

Readme and manuals

Help Manual

Help pageTopics
Barley response to nitrogen fertilizerbarley
Bootstrapping for linear modelsboot_lm
Bootstraping for linear mixed modelsboot_gls boot_lme
Bootstraping for generalized nonlinear models and nonlinear mixed modelsboot_gnls boot_nlme
Bootstrapping for nonlinear modelsboot_nls
Confidence interval methods for (non)-linear modelsconfidence_intervals
object for confidence bands vignette fm1.P.at.x.0.4fm1.P.at.x.0.4
object for confidence bands vignette fm1.P.btfm1.P.bt
object for confidence bands vignette fm1.P.bt.ftfm1.P.bt.ft
object for confidence bands vignette fm2.Lob.btfm2.Lob.bt
object for confidence bands vignette fmm1.btfmm1.bt
Indexes of Agreement TableIA_tab plot.IA_tab print.IA_tab
Information Criteria TableIC_tab
Live fuel moisture contentlfmc
object for confidence bands vignette Lob.bt.peLob.bt.pe
Maize leaf extension rate as a response to temperaturemaizeleafext
Environment to store options and data for nlraanlraa.env
Create a list of nls objects with the option of using nlsLM in addition to nlsnlsLMList nlsLMList.selfStart
Formula method for nls 'LM' list methodnlsLMList.formula
Modified prediciton function based on predict.gampredict_gam
Average predictions from several (non)linear models based on IC weightspredict_gls predict_gnls predict_lme predict_nlme
Average predictions from several (non)linear models based on IC weightspredict2_gam predict_nls
Prediction Bands for Nonlinear Regressionpredict2_nls
R-squared for nonlinear mixed modelsR2M R2M.gls R2M.gnls R2M.lm R2M.lme R2M.nlme R2M.nls
Simulate responses from a generalized additive linear model 'gam'simulate_gam
Simulate fitted values from an object of class 'gls'simulate_gls
Simulate fitted values from an object of class 'gnls'simulate_gnls
Simulate responses from a linear model 'lm'simulate_lm
Simulate values from an object of class 'lme'simulate_lme
Simulate samples from a nonlinear mixed model from fixed effectssimulate_nlme
Simulate fitted values from an object of class 'nlme'simulate_nlme_one
Simulate fitted values from an object of class 'nls'simulate_nls
Sorghum and Maize growth in Greecesm
self start for an asymmetric Gaussian bell-shaped curveagauss SSagauss
self start for a bell-shaped curvebell SSbell
self start for Beta 5-parameter functionbeta5 SSbeta5
self start for the reparameterized Beta growth function with four parametersbg4rp SSbg4rp
self start for Beta Growth Functionbgf bgf2 SSbgf
self start for Beta growth function with four parametersbgf4 SSbgf4
self start for the reparameterized Beta growth functionbgrp SSbgrp
self start for a bilinear Functionblin SSblin
self start for cardinal temperature responsecard3 SScard3
self start for Declining Logistic Functiondlf SSdlf
self start for an exponential functionexpf SSexpf
self start for an exponential-plateau functionexpfp SSexpfp
self start for the exponential-linear growth equationexplin SSexplin
self start for a generalized Michaelis-Menten functiongmicmen SSgmicmen
self start for a harmonic regression modelharm1 SSharm1
self start for Hill Functionhill1 hill2 hill3 SShill SShill1 SShill2 SShill3
self start for linear-plateau functionlinp SSlinp
self start for five-parameter logistic functionlogis5 SSlogis5
self start for modified hyperbola (photosynthesis)moh SSmoh
self start for non-rectangular hyperbola (photosynthesis)nrh SSnrh
self start for plateau-exponential functionpexpf SSpexpf
self start for plateau-linear functionplin SSplin
self start for plateau-quadratic functionpquad SSpquad
self start for plateau-quadratic functionpquad3 SSpquad3
self start for profile decay functionprofd SSprofd
self start for quadratic-plateau functionquadp SSquadp
self start for quadratic-plateau functionquadp3 SSquadp3
self start for quadratic-plateau function (xs)quadp3xs SSquadp3xs
self start for quadratic-plateau-quadratic (QPQ) functionquadpq SSquadpq
self start for a rational curveratio SSratio
self start for Ricker Functionricker SSricker
self start for smooth cardinal temperature responsescard3 SSscard3
self start for temperature responsesharp SSsharp
self start for spherical functionspherical SSspherical
self start for Collatz temperature responseSStemp3 temp3
self start for a trilinear FunctionSStrlin trlin
Summarize a matrix of simulations by their mean (median), sd (mad), and quantilessummary_simulate
Water limitations for Soybean growthswpg
Variance Covariance matrix of for g(n)ls and (n)lme modelsvar_cov