Motivation and model | Statistical inference | Maximum likelihood | Update strategy | Initialization strategy | Complete algorithm | Markov chain Monte Carlo | MCMC algorithm | Full conditional of $\betavec$ | Comparison with other R packages | Appendix: Score and Fisher information | Location coefficients $\betavec$ | Scale coefficients $\gammavec$ | Mixed Fisher information of $\betavec$ and $\gammavec$ | References
Package: lmls 0.1.1
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.
Authors:
lmls_0.1.1.tar.gz
lmls_0.1.1.zip(r-4.7-any)lmls_0.1.1.zip(r-4.6-any)lmls_0.1.1.zip(r-4.5-any)
lmls_0.1.1.tgz(r-4.6-any)lmls_0.1.1.tgz(r-4.5-any)
lmls_0.1.1.tar.gz(r-4.7-any)lmls_0.1.1.tar.gz(r-4.6-any)
lmls_0.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
lmls/json (API)
| # Install 'lmls' in R: |
| install.packages('lmls', repos = c('https://hriebl.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/hriebl/lmls/issues
Pkgdown/docs site:https://hriebl.github.io
Datasets:
- abdom - Abdominal circumference data
Last updated from:16f8568877. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | OK | 159 | ||
| source / vignettes | OK | 186 | ||
| linux-release | OK | 159 | ||
| macos-release | OK | 208 | ||
| macos-oldrel | OK | 180 | ||
| windows-devel | OK | 105 | ||
| windows-release | OK | 109 | ||
| windows-oldrel | OK | 104 | ||
| wasm-release | OK | 106 |
Exports:bootglancelmlsmcmctidy
Dependencies:generics
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Abdominal circumference data | abdom |
| Parametric bootstrap for LMLS | boot |
| Gaussian location-scale regression | lmls |
| Methods for LMLS | coef.lmls fitted.lmls lmls-methods predict.lmls residuals.lmls vcov.lmls |
| MCMC inference for LMLS | mcmc |
| Summary for LMLS | summary.lmls |