XML, lhs, sensitivity, dplyr, readr, purrr, furrr, magrittr,
stats, utils, GenSA, genalg, raster, rstudioapi, sf, tidyr,
methods, tibble, crayon, igraph, stringr, progressr, EasyABC

c(person("Jan", "Salecker", email = "jan.salecker@posteo.de",
role = c("aut"), 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>"),
person("Sebastian", "Hanss", email = "nlrx@mailbox.org",
role = c("cre"), comment = "Package maintainer together with Jan Salecker"))
Jan Salecker [aut] (<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>),
Sebastian Hanss [cre] (Package maintainer together with Jan Salecker)

Saikat DebRoy <saikat@stat.wisc.edu>,
Douglas M. Bates <bates@stat.wisc.edu>, and
Jose C. Pinheiro <jcp@research.bell-labs.com>

Robust Non-Linear Regression using AIC Scores
c(
person("Daniel", "Padfield", email = "d.padfield@exeter.ac.uk", role = c("aut", "cre")),
person("Granville", "Matheson", email = "mathesong@gmail.com", role = "aut"))
Non-linear least squares regression with the Levenberg-Marquardt algorithm using multiple starting values for increasing the chance that the minimum found is the global minimum.
Daniel Padfield [aut, cre],
Granville Matheson [aut]

Adds algorithm="brute-force" and multiple starting values to nls.

Adds algorithm="brute-force" and multiple starting values
to nls.

Adds brute force and multiple starting values to nls.

Nonlinear regression in predictive microbiology
Florent Baty <florent.baty@gmail.com> and Marie-Laure
Delignette-Muller <marielaure.delignettemuller@vetagro-sup.fr>
Data sets and nonlinear regression models dedicated to predictive microbiology