Higher Order Inference for Nonlinear Heteroscedastic Models
S original by Alessandra R. Brazzale
<alessandra.brazzale@unimore.it> and Ruggero Bellio
<ruggero.bellio@dss.uniud.it>.  R port by Alessandra R.
Brazzale <alessandra.brazzale@unimore.it>, following earlier
work by Douglas Bates.
Likelihood inference based on higher order approximations
for nonlinear models with possibly non constant variance

S original by Alessandra R. Brazzale <alessandra.brazzale@unipd.it>
and Ruggero Bellio <ruggero.bellio@uniud.it>.  R port by Alessandra R.
Brazzale <alessandra.brazzale@unipd.it>, following earlier work by
Douglas Bates.

Likelihood inference based on higher order approximations
for nonlinear models with possibly non constant variance.

Roger Koenker <rkoenker@uiuc.edu>,
Philippe Grosjean <phgrosjean@sciviews.org>

Nonlinear quantile regression routines -- Defunct

Non-Linear Relative Risk Estimation and Plotting
person("Yiqiang", "Zhan", email = "zhanyiqiang@gmail.com", role = c("aut", "cre"))
Estimate the non-linear odds ratio and plot it against a continuous exposure.

Datasets and functions for nonlinear regression. Support software for the book "Nonlinear regression with R".
R (>= 2.0.0), alr3, car, drc, HydroMe, lattice, lmtest, MASS, NISTnls, nlme, nls2, nlstools, NRAIA, sandwich

Datasets and functions for nonlinear regression. Support
software for the book "Nonlinear regression with R".
R (>= 2.0.0), alr3, car, drc, HydroMe, lattice, lmtest, MASS,
NISTnls, nlme, nls2, nlstools, NRAIA, sandwich

Datasets and functions for non-linear regression, supporting software for the book "Non-linear regression with R".
R (>= 2.0.0), alr3, boot, car, drc, HydroMe, lattice, lmtest, MASS, NISTnls, nlme, nlstools, nls2, plotrix, sandwich

Orphaned on 2015-07-08 at the request of the
maintainer: likely to be orphaned soon.

Setup, Run and Analyze 'NetLogo' Model Simulations from 'R' via
'XML'
c(person("Jan", "Salecker", email = "jsaleck@gwdg.de",
role = c("aut", "cre"), comment = c(ORCID = '0000-0002-9000-4229')),
person("Marco", "Sciaini", email = "sciaini.marco@gmail.com", role = c("aut"), comment = c(ORCID = '0000-0002-3042-5435')),
person("Marina", "Papadopoulou", role = "rev",
comment = "Marina reviewed the package for ropensci, see <https://github.com/ropensci/software-review/issues/262>"))
The purpose of this package is to provide tools to setup, run and analyze 'NetLogo' (<https://ccl.northwestern.edu/netlogo/>) model simulations in 'R'.
'nlrx' experiments use a similar structure as 'NetLogos' Behavior Space experiments.
However, 'nlrx' offers more flexibility and additional tools for running and analyzing complex simulation designs and sensitivity analyses.
The user defines all information that is needed in an intuitive framework, using class objects.
Experiments are submitted from 'R' to 'NetLogo' via 'XML' files that are dynamically written, based on specifications defined by the user.
By nesting model calls in future environments, large simulation design with many runs can be executed in parallel.
This also enables simulating 'NetLogo' experiments on remote HPC machines.
In order to use this package, 'Java' and 'NetLogo' (>= 5.3.1) need to be available on the executing system.
XML, lhs, sensitivity, dplyr, readr, purrr, furrr, magrittr,
stats, utils, GenSA, genalg, raster, rstudioapi, sf, tidyr,
methods, tibble, igraph, stringr
Jan Salecker [aut, cre] (<https://orcid.org/0000-0002-9000-4229>),
Marco Sciaini [aut] (<https://orcid.org/0000-0002-3042-5435>),
Marina Papadopoulou [rev] (Marina reviewed the package for ropensci,
see <https://github.com/ropensci/software-review/issues/262>)