Package: onls 0.1-4

onls: Orthogonal Nonlinear Least-Squares Regression

Fits two-dimensional data by means of orthogonal nonlinear least-squares using Levenberg-Marquardt minimization and provides functionality for fit diagnostics and plotting. Delivers the same results as the 'ODRPACK' Fortran implementation described in Boggs et al. (1989) <doi:10.1145/76909.76913>, but is implemented in pure R.

Authors:Andrej-Nikolai Spiess [aut, cre]

onls_0.1-4.tar.gz
onls_0.1-4.zip(r-4.7)onls_0.1-4.zip(r-4.6)onls_0.1-4.zip(r-4.5)
onls_0.1-4.tgz(r-4.6-any)onls_0.1-4.tgz(r-4.5-any)
onls_0.1-4.tar.gz(r-4.7-any)onls_0.1-4.tar.gz(r-4.6-any)
onls_0.1-4.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
onls/json (API)
NEWS

# Install 'onls' in R:
install.packages('onls', repos = c('https://anspiess.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.90 score 2 stars 20 scripts 587 downloads 1 mentions 8 exports 1 dependencies

Last updated from:1255e0a14a. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK101
source / vignettesOK207
linux-release-x86_64OK93
macos-release-arm64OK82
macos-oldrel-arm64OK94
windows-develOK99
windows-releaseOK78
windows-oldrelOK79
wasm-releaseOK79

Exports:check_odeviance_ologLik_oNISTonlsresiduals_ox0y0

Dependencies:minpack.lm

Introduction

Rendered fromonls.Rnwusingutils::Sweaveon May 29 2026.

Last update: 2022-10-31
Started: 2015-09-09