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lmls  

Gaussian Location-Scale Regression
View on CRAN: Click here


Download and install lmls package within the R console
Install from CRAN:
install.packages("lmls")

Install from Github:
library("remotes")
install_github("cran/lmls")

Install by package version:
library("remotes")
install_version("lmls", "0.1.1")



Attach the package and use:
library("lmls")
Maintained by
Hannes Riebl
[Scholar Profile | Author Map]
First Published: 2022-01-18
Latest Update: 2022-01-18
Description:
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) and Nesterov (2009) ), a parametric bootstrap algorithm, and diagnostic plots for the model class.
How to cite:
Hannes Riebl (2022). lmls: Gaussian Location-Scale Regression. R package version 0.1.1, https://cran.r-project.org/web/packages/lmls. Accessed 06 Apr. 2025.
Previous versions and publish date:
0.1.0 (2022-01-18 09:32)
Other packages that cited lmls R package
View lmls citation profile
Other R packages that lmls depends, imports, suggests or enhances
Complete documentation for lmls
Functions, R codes and Examples using the lmls R package
Some associated functions: abdom . boot . lmls-methods . lmls . mcmc . reexports . summary.lmls . 
Some associated R codes: abdom.R . boot.R . broom.R . lmls-helpers.R . lmls.R . mcmc.R . methods.R . testthat-helpers.R .  Full lmls package functions and examples
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