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nlraa: R package for Nonlinear Regression for Agricultural

Applications

Documentation

NOTE: the vignettes (nlraa-Oddi-LFMC and nlraa-AgronJ-paper) that used to be distributed with the package have been moved to the documentation above because of CRAN size limits.

Nonlinear Models (video) - part I

Nonlinear Models (video) - part II

Nonlinear Models (video) - part III

To install

library(remotes)
remotes::install_github("femiguez/nlraa")
library(nlraa)

This package supports the following publications:

  1. Archontoulis, S. V., and F. E. Miguez. 2015. Nonlinear Regression Models and Applications in Agricultural Research. Agron. J. 107:786-798.
    https://doi.org/10.2134/agronj2012.0506

  2. Miguez, F., S. Archontoulis, H. Dokoohaki 2018. Chapter 15: Nonlinear Regression Models and Applications. In: B. Glaz, K. M. Yeater, editors, Applied Statistics in Agricultural, Biological, and Environmental Sciences, ASA, CSSA, and SSSA, Madison, WI. p. 401-448.
    https://doi.org/10.2134/appliedstatistics.2016.0003

  3. Oddi et. al. (2019). A nonlinear mixed-effects modelling approach for ecological data: Using temporal dynamics of vegetation moisture as an example. Ecology and Evolution.
    https://doi.org/10.1002/ece3.5543

Some recent publications which cite this package:

14. Positive associations of soil organic matter and crop yields across a regional network of working farms. Emily E. Oldfield,Mark A. Bradford,Abigail J. Augarten, Eric T. Cooley, Amber M. Radatz, Timothy Radatz, Matthew D. Ruark. Soil Science Society of America. 2021. https://doi.org/10.1002/saj2.20349

13. Improvement of the Mass-Rearing Protocols for the South American Fruit Fly for Application of the Sterile Insect Technique. Mastrangelo et al. Insects 2021, 12(7), 622; https://doi.org/10.3390/insects12070622

12. High-yielding sugarcane in tropical Brazil – Integrating field experimentation and modelling approach for assessing variety performances. Henrique Boriolo Dias, Geoff Inman-Bamber, Paulo Cesar Sentelhas, Yvette Everingham, Rodrigo Bermejo, Diomedes Christodoulou. Field Crops Research. 2021. https://doi.org/10.1016/j.fcr.2021.108323.

11. Evaluation of mehlich-3 for determination of cation exchange capacity in Kansas soils. Edmond Bryan Rutter, Dorivar Ruiz Diaz,Lynn M. Hargrave. 2021. Soil Science Society of America. https://doi.org/10.1002/saj2.20354

10. Effects of human disturbance on postnatal growth and baseline corticosterone in a long-lived bird. Hannah Watson, Pat Monaghan, Britt J Heidinger, Mark Bolton. Conservation Physiology, Volume 9, Issue 1, 2021. https://doi.org/10.1093/conphys/coab052

9. The use of R in photosynthesis research. Yasi Liu, Xiangping Wang, Dayong Fan and Jiangshan Lai. Functional Plant Biology 1-8 https://doi.org/10.1071/FP21102

8. Topographic effects on soil microclimate and surface cover crop residue decomposition in rolling cropland. Sam J. Leuthold, Dan Quinn, Fernando Miguez, Ole Wendroth, Monsterrat Salmerón, Hanna Poffenbarger. Agriculture, Ecosystems & Environment, Volume 320, 2021. https://doi.org/10.1016/j.agee.2021.107609.

7. Long-term no-till increases soil nitrogen mineralization but does not affect optimal corn nitrogen fertilization practices relative to inversion tillage. Lucas Pecci Canisares, John Grove, Fernando Miguez and Hanna Poffenbarger. Soil and Tillage Research. Volume 213. 2021. 105080. https://doi.org/10.1016/j.still.2021.105080.

6. Rotating maize reduces the risk and rate of nitrate leaching. Heather Randolph Pasley, Nichols Virginia, Michael J Castellano, Matthew J Helmers, Mitchell E Baum, Eileen J Kladivko and Sotirios Archontoulis. 2021. Environmental Research Letters. https://doi.org/10.1088/1748-9326/abef8f

5. Abendroth, L.J., Miguez, F.E., Castellano, M.J., Carter, P.R., Messina, C.D., Dixon, P.M. and Hatfield, J.L. (2021), Lengthening of maize maturity time is not a widespread climate change adaptation strategy in the US Midwest. Glob Change Biol. https://doi.org/10.1111/gcb.15565

4. Interactive effect of glyphosate-based herbicides and organic soil layer thickness on growth and reproduction of the tropical earthworm Pontoscolex corethrurus (Müller, 1857). Garcia-Perez et al. (2020). https://doi.org/10.1016/j.apsoil.2020.103648

3. Cuando la variabilidad varía: Heterocedasticidad y funciones de varianza. Oddi, F. J., Miguez, F. E., Benedetti, G. G., & Garibaldi, L. A. (2020). Ecología Austral; 30; 438-453.

2. Short-term effects of integrated tillage systems and cover crop on agronomic response and soil health in North Central Iowa. Alex Cleveringa. 2020. MS Thesis. Iowa State University.

1. The Effects of Agronomic Management and 40 Years of Variety Release on Soybean Seed Fill and Yield Components. Kathryn Graf. 2018. MS thesis. Purdue University.

Other publications where we have used nonlinear mixed models:

  1. Fernando E. Miguez, María Bonita Villamil, Stephen P. Long, Germán A. Bollero, Meta-analysis of the effects of management factors on Miscanthus × giganteus growth and biomass production, Agricultural and Forest Meteorology, Volume 148, Issues 8–9, 2008, Pages 1280-1292, ISSN 0168-1923,
    https://doi.org/10.1016/j.agrformet.2008.03.010.
    Supporting information:
    http://miguezlab.agron.iastate.edu/OldWebsite/Research/Miscanthus/MetaMiscan.tar.gz

  2. Eichenberger, S., F. Miguez, J. Edwards, and A. Knapp. 2015. Changes in Kernel Filling with Selection for Grain Yield in a Maize Population. Crop Sci. 55:521-526.
    https://doi.org/10.2135/cropsci2014.07.0462

  3. Stein, M., F. Miguez, and J. Edwards. 2016. Effects of Plant Density on Plant Growth before and after Recurrent Selection in Maize. Crop Sci. 56:2882-2894.
    https://doi.org/10.2135/cropsci2015.09.0599

Talks:

2008 ACS meeting.

Slides:
http://miguezlab.agron.iastate.edu/OldWebsite/Research/Talks/ASA_Miguez.pdf

Data and code:
http://miguezlab.agron.iastate.edu/OldWebsite/Research/Talks/Barley.zip

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Version

Install

install.packages('nlraa')

Monthly Downloads

718

Version

1.2

License

GPL-3

Maintainer

Fernando Miguez

Last Published

February 14th, 2022

Functions in nlraa (1.2)

SSbell

self start for a bell-shaped curve
SSbeta5

self start for Beta 5-parameter function
SSbgf4

self start for Beta growth function with four parameters
IA_tab

Indexes of Agreement Table
SSbgf

self start for Beta Growth Function
IC_tab

Information Criteria Table
SSbg4rp

self start for the reparameterized Beta growth function with four parameters
Lob.bt.pe

object for confidence bands vignette Lob.bt.pe
R2M

R-squared for nonlinear mixed models
SSbgrp

self start for the reparameterized Beta growth function
SSmoh

self start for modified hyperbola (photosynthesis)
SSblin

self start for a bilinear Function
SSsharp

self start for temperature response
SSdlf

self start for Declining Logistic Function
SStemp3

self start for Collatz temperature response
SSricker

self start for Ricker Function
SSratio

self start for a rational curve
SSnrh

self start for non-rectangular hyperbola (photosynthesis)
SSpquad3

self start for plateau-quadratic function
SSpquad

self start for plateau-quadratic function
SSpexpf

self start for plateau-exponential function
SSlinp

self start for linear-plateau function
SSlogis5

self start for five-parameter logistic function
boot_lm

Bootstrapping for linear models
simulate_lm

SSprofd

self start for profile decay function
SSexpfp

self start for an exponential-plateau function
fm1.P.at.x.0.4

object for confidence bands vignette fm1.P.at.x.0.4
SSquadp

self start for quadratic-plateau function
SSexpf

self start for an exponential function
SSexplin

self start for the exponential-linear growth equation
fm1.P.bt

object for confidence bands vignette fm1.P.bt
boot_lme

Bootstraping for linear mixed models
lfmc

Live fuel moisture content
SSplin

self start for plateau-linear function
fmm1.bt

object for confidence bands vignette fmm1.bt
nlraa.env

Environment to store options and data for nlraa
boot_nls

Bootstrapping for nonlinear models
boot_nlme

Bootstraping for generalized nonlinear models and nonlinear mixed models
maizeleafext

Maize leaf extension rate as a response to temperature
SStrlin

self start for a trilinear Function
nlsLMList.formula

Formula method for nls 'LM' list method
nlsLMList

Create a list of nls objects with the option of using nlsLM in addition to nls
simulate_gam

barley

Barley response to nitrogen fertilizer
sm

Sorghum and Maize growth in Greece
simulate_nlme_one

summary_simulate

Summarize a matrix of simulations by their mean (median), sd (mad), and quantiles
SShill

self start for Hill Function
fm2.Lob.bt

object for confidence bands vignette fm2.Lob.bt
simulate_nls

fm1.P.bt.ft

object for confidence bands vignette fm1.P.bt.ft
SSquadp3

self start for quadratic-plateau function
predict2_nls

Prediction Bands for Nonlinear Regression
SSquadp3xs

self start for quadratic-plateau function (xs)
predict_gam

Modified prediciton function based on predict.gam
simulate_lme

simulate_nlme

Simulate samples from a nonlinear mixed model from fixed effects
simulate_gnls

simulate_gls

swpg

Water limitations for Soybean growth
var_cov

Variance Covariance matrix of for g(n)ls and (n)lme models
predict_nlme

Average predictions from several (non)linear models based on IC weights
predict_nls

Average predictions from several (non)linear models based on IC weights