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melt

Multiple empirical likelihood tests

https://github.com/ropensci/melt

Science Score: 39.0%

This score indicates how likely this project is to be science-related based on various indicators:

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    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ✓
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    Found 4 DOI reference(s) in README
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Keywords

cran r r-package rstats
Last synced: 9 months ago · JSON representation

Repository

Multiple empirical likelihood tests

Basic Info
Statistics
  • Stars: 15
  • Watchers: 4
  • Forks: 1
  • Open Issues: 0
  • Releases: 5
Topics
cran r r-package rstats
Created over 5 years ago · Last pushed about 2 years ago
Metadata Files
Readme Changelog Contributing License Codemeta

README.Rmd 

---
output: github_document
---



```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  dpi = 300,
  fig.path = "man/figures/README-",
  out.width = "100%"
)
```

# melt melt website


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## Overview

melt provides a unified framework for data analysis with empirical likelihood methods.
A collection of functions is available to perform multiple empirical likelihood tests and construct confidence intervals for various models in 'R'.
melt offers an easy-to-use interface and flexibility in specifying hypotheses and calibration methods, extending the framework to simultaneous inferences.
The core computational routines are implemented with the 'Eigen' 'C++' library and 'RcppEigen' interface, with 'OpenMP' for parallel computation. 
Details of the testing procedures are provided in [Kim, MacEachern, and Peruggia (2023)](https://doi.org/10.1080/10485252.2023.2206919). 
The package has a companion paper by [Kim, MacEachern, and Peruggia (2024)](https://doi.org/10.18637/jss.v108.i05).
This work was supported by the U.S. National Science Foundation under Grants No. [SES-1921523](https://www.nsf.gov/awardsearch/showAward?AWD_ID=1921523) and [DMS-2015552](https://www.nsf.gov/awardsearch/showAward?AWD_ID=2015552).


## Installation

You can install the latest stable release of melt from CRAN.

```{r, eval = FALSE}
install.packages("melt")
```

You can install the development version of melt from GitHub or [R-universe](http://ropensci.r-universe.dev/ui/#package:melt).

```{r, eval = FALSE}
# install.packages("pak")
pak::pak("ropensci/melt")
```

```{r eval = FALSE}
install.packages("melt", repos = "https://ropensci.r-universe.dev")
```


## Main functions

melt provides an intuitive API for performing the most common data analysis tasks:

* `el_mean()` computes empirical likelihood for the mean.
* `el_lm()` fits a linear model with empirical likelihood.
* `el_glm()` fits a generalized linear model with empirical likelihood.
* `confint()` computes confidence intervals for model parameters.
* `confreg()` computes confidence region for model parameters.
* `elt()` tests a hypothesis with various calibration options.
* `elmt()` performs multiple testing simultaneously.


## Usage
```{r usage, eval = TRUE}
library(melt)
set.seed(971112)

## Test for the mean
data("precip")
(fit <- el_mean(precip, par = 30))


## Adjusted empirical likelihood calibration
elt(fit, rhs = 30, calibrate = "ael")


## Bootstrap calibration
elt(fit, rhs = 30, calibrate = "boot")


## F calibration
elt(fit, rhs = 30, calibrate = "f")


## Linear model
data("mtcars")
fit_lm <- el_lm(mpg ~ disp + hp + wt + qsec, data = mtcars)
summary(fit_lm)
cr <- confreg(fit_lm, parm = c("disp", "hp"), npoints = 200)
plot(cr)
data("clothianidin")
fit2_lm <- el_lm(clo ~ -1 + trt, data = clothianidin)
summary(fit2_lm)
confint(fit2_lm)


## Generalized linear model
data("thiamethoxam")
fit_glm <- el_glm(visit ~ log(mass) + fruit + foliage + var + trt,
  family = quasipoisson(link = "log"), data = thiamethoxam,
  control = el_control(maxit = 100, tol = 1e-08, nthreads = 4)
)
summary(fit_glm)


## Test of no treatment effect
contrast <- c(
  "trtNaked - trtFungicide", "trtFungicide - trtLow", "trtLow - trtHigh"
)
elt(fit2_lm, lhs = contrast)


## Multiple testing
contrast2 <- rbind(
  c(0, 0, 0, 0, 0, 1, 0, 0),
  c(0, 0, 0, 0, 0, 0, 1, 0),
  c(0, 0, 0, 0, 0, 0, 0, 1)
)
elmt(fit_glm, lhs = contrast2)
```

---
Please note that this package is released with a [Contributor Code of Conduct](https://ropensci.org/code-of-conduct/). By contributing to this project, you agree to abide by its terms.

Owner

  • Name: rOpenSci
  • Login: ropensci
  • Kind: organization
  • Email: info@ropensci.org
  • Location: Berkeley, CA

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GitHub Events

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  • Issues event: 4
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Last Year
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  • Avg Commits per committer: 141.75
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Past Year
  • Commits: 20
  • Committers: 1
  • Avg Commits per committer: 20.0
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Top Committers
Name Email Commits
markean m****n@p****m 531
markean m****5@g****m 31
Eunseop Kim 4****n 4
kime47 k****p@g****m 1
Committer Domains (Top 20 + Academic)
gene.com: 1

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Last synced: 10 months ago

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  • Total issues: 8
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  • Average time to close issues: 8 days
  • Average time to close pull requests: 4 days
  • Total issue authors: 3
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  • Average comments per issue: 0.38
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  • Bot issues: 1
  • Bot pull requests: 0
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  • Average time to close issues: 5 days
  • Average time to close pull requests: N/A
  • Issue authors: 1
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  • Average comments per issue: 2.0
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View more stats
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  • markean (5)
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enhancement (1)
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Packages

  • Total packages: 1
  • Total downloads:
    • cran 1,120 last-month
  • Total dependent packages: 2
  • Total dependent repositories: 1
  • Total versions: 19
  • Total maintainers: 1
cran.r-project.org: melt

Multiple Empirical Likelihood Tests

  • Versions: 19
  • Dependent Packages: 2
  • Dependent Repositories: 1
  • Downloads: 1,120 Last month
Rankings
Downloads: 13.6%
Stargazers count: 17.4%
Average: 20.9%
Forks count: 21.0%
Dependent repos count: 23.8%
Dependent packages count: 28.6%
Maintainers (1)
markean@pm.me
Last synced: 10 months ago

Dependencies

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.github/workflows/test-coverage.yaml actions
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DESCRIPTION cran
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  • graphics * imports
  • methods * imports
  • stats * imports
  • utils * imports
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