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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.
Getting started
Browse package contents
Package details |
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| Author | Hannes Riebl [aut, cre] |
| Maintainer | Hannes Riebl <hriebl@posteo.de> |
| License | MIT + file LICENSE |
| Version | 0.1.1 |
| URL | https://hriebl.github.io/lmls/ https://github.com/hriebl/lmls |
| Package repository | View on CRAN |
| Installation |
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