Description: Methods for obtaining improved estimates of non-linear cross-validated risks are obtained using targeted minimum loss-based estimation, estimating equations, and one-step estimation (Benkeser, Petersen, van der Laan (2019), <doi:10.1080/01621459.2019.1668794>). Cross-validated area under the receiver operating characteristics curve (LeDell, Petersen, van der Laan (2015), <doi:10.1214/15-EJS1035>) and other metrics are included.
Packaged: 2020-02-23 17:11:12 UTC; davidbenkeser

Title: Nonlinear Regression Modelling using Robust Methods
Description: Non-Linear Robust package is developed to handle the problem of
outliers in nonlinear regression,    using robust statistics. It covers
classic methods in nonlinear regression as well. It has facilities to fit
models in the case of auto correlated and heterogeneous variance cases,
while it include tools to detecting outliers in nonlinear regression.
(Riazoshams H, Midi H, and Ghilagaber G, (2018, ISBN:978-1-118-73806-1).
Robust Nonlinear Regression, with Application using R, Joh Wiley and Sons.)
Imports: MASS,nlme, robcor, TSA,tseries,stats, GA, quantreg

Robust Nonlinear Regression, with Application using R, John Wiley and Sons.)

Authors@R: c(person("Fernando", "Miguez", email = "femiguez@iastate.edu", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-4627-8329")),
person("José", "Pinheiro", role = c("ctb","cph"), comment = "author of nlme::nlsList"),
person("Douglas", "Bates", role = c("ctb","cph"), comment = "author of nlme::nlsList"),
person("R-core", email = "R-core@R-project.org", role = c("ctb", "cph")))
Title: Nonlinear Regression for Agricultural Applications
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) <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. Eighteen 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> 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'. One of the main benefits is that these functions can be integrated in the modeling framework of the 'nlme' package. It also provides three vignettes with extended examples.
Suggests: bbmle, emmeans, ggplot2, HydroMe, lattice, minpack.lm,
Packaged: 2020-01-09 21:39:02 UTC; fernandomiguez
Author: Fernando Miguez [aut, cre] (<https://orcid.org/0000-0002-4627-8329>),
José Pinheiro [ctb, cph] (author of nlme::nlsList),
Douglas Bates [ctb, cph] (author of nlme::nlsList),