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.

lmls: Gaussian Location-Scale Regression

The Gaussian location-scale regression model is a multi-predictor model with explanatory variables for the mean (= location) and the standard deviation (= scale) of a response variable. This package implements maximum likelihood and Markov chain Monte Carlo (MCMC) inference (using algorithms from Girolami and Calderhead (2011) <doi:10.1111/j.1467-9868.2010.00765.x> and Nesterov (2009) <doi:10.1007/s10107-007-0149-x>), a parametric bootstrap algorithm, and diagnostic plots for the model class.

Version: 0.1.0
Depends: R (≥ 3.5.0)
Imports: generics (≥ 0.1.0)
Suggests: bookdown, coda, covr, ggplot2, knitr, mgcv, mvtnorm, numDeriv, patchwork, rmarkdown, testthat (≥ 3.0.0)
Published: 2022-01-18
DOI: 10.32614/CRAN.package.lmls
Author: Hannes Riebl [aut, cre]
Maintainer: Hannes Riebl <hriebl at uni-goettingen.de>
License: MIT + file LICENSE
URL: https://hriebl.github.io/lmls/
NeedsCompilation: no
Materials: README NEWS
CRAN checks: lmls results [issues need fixing before 2024-11-26]

Documentation:

Reference manual: lmls.pdf
Vignettes: Location-Scale Regression and the *lmls* Package

Downloads:

Package source: lmls_0.1.0.tar.gz
Windows binaries: r-devel: lmls_0.1.0.zip, r-release: lmls_0.1.0.zip, r-oldrel: lmls_0.1.0.zip
macOS binaries: r-release (arm64): lmls_0.1.0.tgz, r-oldrel (arm64): lmls_0.1.0.tgz, r-release (x86_64): lmls_0.1.0.tgz, r-oldrel (x86_64): lmls_0.1.0.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=lmls 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.