The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.

sclr: Scaled Logistic Regression

Maximum likelihood estimation of the scaled logit model parameters proposed in Dunning (2006) <doi:10.1002/sim.2282>.

Version: 0.3.1
Depends: R (≥ 3.6.0)
Imports: broom, tibble, dplyr, rlang, stats, purrr
Suggests: knitr, rmarkdown, testthat (≥ 2.1.0)
Published: 2020-03-02
DOI: 10.32614/CRAN.package.sclr
Author: Arseniy Khvorov [aut, cre]
Maintainer: Arseniy Khvorov <khvorov45 at gmail.com>
License: MIT + file LICENSE
URL: https://khvorov45.github.io/sclr/
NeedsCompilation: no
Materials: README NEWS
CRAN checks: sclr results

Documentation:

Reference manual: sclr.pdf
Vignettes: Model specification, log-likelihood, scores and second derivatives
Usage

Downloads:

Package source: sclr_0.3.1.tar.gz
Windows binaries: r-devel: sclr_0.3.1.zip, r-release: sclr_0.3.1.zip, r-oldrel: sclr_0.3.1.zip
macOS binaries: r-release (arm64): sclr_0.3.1.tgz, r-oldrel (arm64): sclr_0.3.1.tgz, r-release (x86_64): sclr_0.3.1.tgz, r-oldrel (x86_64): sclr_0.3.1.tgz
Old sources: sclr archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=sclr to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.