lmls
0.1.1Gaussian Location-Scale Regression
Overview
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.
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Health
- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
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- Examples that run
- 100%
- Documented parameters
- 95%
- Return-value docs
- 75%
- References docs
- 29%
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People & History
2 releases. Pick two to compare their code metrics. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- 0.1.1Latest
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- 0.1.02022-01-18
- RR 4.1.0 released · 2021-05-18
Package metadata
- First published
- 2022-01-18
- Total releases
- 2 / 4 yrs
- License
- MIT + file LICENSE OSI
- Minimum R
- ≥ 3.5.0
- Bundled data
- 1.3 KB / 1 file
- Download size
- 334 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet