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lmls

Gaussian location-scale regression

https://github.com/hriebl/lmls

Science Score: 36.0%

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    Low similarity (17.8%) to scientific vocabulary

Keywords

r r-package
Last synced: 10 months ago · JSON representation

Repository

Gaussian location-scale regression

Basic Info
Statistics
  • Stars: 3
  • Watchers: 1
  • Forks: 1
  • Open Issues: 0
  • Releases: 1
Topics
r r-package
Created over 4 years ago · Last pushed over 1 year ago
Metadata Files
Readme Changelog License

README.Rmd 

---
output: github_document
---



```{r setup, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%",
  dpi = 150
)

library(ggplot2)

theme_set(theme_bw(base_size = 11))

theme_update(
  legend.position = "none",
  axis.text = element_text(color = "black", size = 11),
  axis.title.x.bottom = element_text(margin = margin(t = 11)),
  axis.title.y.left = element_text(margin = margin(r = 11))
)
```

# lmls


[![R CMD check](https://github.com/hriebl/lmls/actions/workflows/check-standard.yaml/badge.svg)](https://github.com/hriebl/lmls/actions)
[![Codecov test coverage](https://codecov.io/gh/hriebl/lmls/branch/main/graph/badge.svg)](https://app.codecov.io/gh/hriebl/lmls?branch=main)


*lmls* is an R package for working with linear models for location and scale. These models are multi-predictor regression models with explanatory variables for the mean (= the location) and the standard deviation (= the scale) of a normally distributed response variable. They are special cases of generalized additive models for location, scale and shape (GAMLSS), as described by [Rigby and Stasinopoulos (2005)](https://doi.org/10.1111/j.1467-9876.2005.00510.x).

The *lmls* package provides functions for maximum likelihood and Markov chain Monte Carlo (MCMC) estimation, a parametric bootstrap algorithm, and some diagnostic plots. It was written for the "Advanced Statistical Programming" course at Göttingen University. Feel free to use the package and vignette as an introduction to location-scale regression, or as a basis for the implementation of additional inference algorithms and model extensions.

## Installation

You can install the released version of *lmls* from [CRAN](https://cran.r-project.org/package=lmls) with:

``` r
install.packages("lmls")
```

Or install the development version from GitHub:

``` r
# install.packages("remotes")
remotes::install_github("hriebl/lmls")
```

## Example

The *lmls* package comes with the *abdom* dataset (which it borrows from the *gamlss.data* package). The dataset consists of only two variables: the size of 610 fetuses (as measurements of their abdominal circumference taken from ultrasound scans) and their gestational age ranging from 12 to 42 weeks.

To estimate an LMLS with a quadratic effect of the babies' age on their average size and a linear effect on the log-standard deviation, run this code:

```{r abdom-model}
library(ggplot2)
library(lmls)

m <- lmls(y ~ poly(x, 2), ~ x, data = abdom)
```

You can now use *ggplot2* to visualize the model:

```{r abdom-plot}
df <- abdom
df$mu <- predict(m, type = "response", predictor = "location")
df$sigma <- predict(m, type = "response", predictor = "scale")
df$upper <- df$mu + 1.96 * df$sigma
df$lower <- df$mu - 1.96 * df$sigma

ggplot(df, aes(x, y)) +
  geom_point(color = "darkgray", size = 1) +
  geom_line(aes(y = mu), linewidth = 0.7) +
  geom_line(aes(y = upper), linewidth = 0.3) +
  geom_line(aes(y = lower), linewidth = 0.3) +
  xlab("Age [weeks]") +
  ylab("Size [mm]")
```

## Vignette

For more details, see the [package vignette](https://hriebl.github.io/lmls/articles/lmls.pdf).

Owner

  • Name: Hannes Riebl
  • Login: hriebl
  • Kind: user
  • Location: Lübeck

GitHub Events

Total
  • Issue comment event: 2
  • Push event: 18
  • Pull request event: 4
  • Fork event: 1
Last Year
  • Issue comment event: 2
  • Push event: 18
  • Pull request event: 4
  • Fork event: 1

Committers

Last synced: over 2 years ago

All Time
  • Total Commits: 50
  • Total Committers: 1
  • Avg Commits per committer: 50.0
  • Development Distribution Score (DDS): 0.0
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Hannes Riebl h****l@u****e 50
Committer Domains (Top 20 + Academic)
uni-goettingen.de: 1

Issues and Pull Requests

Last synced: 11 months ago

All Time
  • Total issues: 0
  • Total pull requests: 3
  • Average time to close issues: N/A
  • Average time to close pull requests: 3 months
  • Total issue authors: 0
  • Total pull request authors: 2
  • Average comments per issue: 0
  • Average comments per pull request: 0.67
  • Merged pull requests: 2
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 2
  • Average time to close issues: N/A
  • Average time to close pull requests: 7 days
  • Issue authors: 0
  • Pull request authors: 1
  • Average comments per issue: 0
  • Average comments per pull request: 1.0
  • Merged pull requests: 2
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
Pull Request Authors
  • hadley (4)
  • olivroy (2)
Top Labels
Issue Labels
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Packages

  • Total packages: 1
  • Total downloads:
    • cran 605 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 2
  • Total maintainers: 1
cran.r-project.org: lmls

Gaussian Location-Scale Regression

  • Versions: 2
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 605 Last month
Rankings
Forks count: 28.8%
Dependent packages count: 29.8%
Stargazers count: 31.7%
Dependent repos count: 35.5%
Average: 40.8%
Downloads: 78.1%
Maintainers (1)
hriebl@posteo.de
Last synced: 11 months ago

Dependencies

DESCRIPTION cran
  • R >= 3.5.0 depends
  • generics >= 0.1.0 imports
  • bookdown * suggests
  • coda * suggests
  • covr * suggests
  • ggplot2 * suggests
  • knitr * suggests
  • mgcv * suggests
  • mvtnorm * suggests
  • numDeriv * suggests
  • patchwork * suggests
  • rmarkdown * suggests
  • testthat >= 3.0.0 suggests
.github/workflows/check-standard.yaml actions
  • actions/checkout v4 composite
  • r-lib/actions/check-r-package v2 composite
  • r-lib/actions/setup-pandoc v2 composite
  • r-lib/actions/setup-r v2 composite
  • r-lib/actions/setup-r-dependencies v2 composite
  • r-lib/actions/setup-tinytex v2 composite
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  • actions/checkout v4 composite
  • r-lib/actions/setup-pandoc v2 composite
  • r-lib/actions/setup-r v2 composite
  • r-lib/actions/setup-r-dependencies v2 composite
  • r-lib/actions/setup-tinytex v2 composite
.github/workflows/test-coverage.yaml actions
  • actions/checkout v4 composite
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