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