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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
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:

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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.
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