Package: RGN 1.0.0

David McInerney

RGN: Robust-Gauss Newton (RGN) Optimization of Sum-of-Squares Objective Function

Implementation of the Robust Gauss-Newton (RGN) algorithm, designed for solving optimization problems with a sum of least squares objective function. For algorithm details please refer to Qin et. al. (2018) <doi:10.1029/2017WR022488>.

Authors:David McInerney [cre, aut], Michael Leonard [aut], Dmitri Kavetski [aut], Youwei Qin [aut], George Kuczera [aut]

RGN_1.0.0.tar.gz
RGN_1.0.0.zip(r-4.7)RGN_1.0.0.zip(r-4.6)RGN_1.0.0.zip(r-4.5)
RGN_1.0.0.tgz(r-4.6-x86_64)RGN_1.0.0.tgz(r-4.6-arm64)RGN_1.0.0.tgz(r-4.5-x86_64)RGN_1.0.0.tgz(r-4.5-arm64)
RGN_1.0.0.tar.gz(r-4.7-arm64)RGN_1.0.0.tar.gz(r-4.7-x86_64)RGN_1.0.0.tar.gz(r-4.6-arm64)RGN_1.0.0.tar.gz(r-4.6-x86_64)
RGN_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
RGN/json (API)

# Install 'RGN' in R:

install.packages('RGN', repos = c('https://climateanalytics.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/climateanalytics/rgn/issues

Uses libs:

fortran– Runtime library for GNU Fortran applications

Datasets:

BassRiverData - Hydrological data for Bass River catchment in Victoria, Australia

On CRAN:

fortran

3.18 score 1 packages 2 scripts 195 downloads 2 exports 0 dependencies

Last updated from:4a82b7f4ed. Checks:13 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	OK	129
linux-devel-x86_64	OK	123
source / vignettes	OK	160
linux-release-arm64	OK	173
linux-release-x86_64	OK	125
macos-release-arm64	OK	150
macos-release-x86_64	OK	191
macos-oldrel-arm64	OK	168
macos-oldrel-x86_64	OK	310
windows-devel	OK	116
windows-release	OK	101
windows-oldrel	OK	107
wasm-release	OK	96