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README.Rmd
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README.Rmd
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---
output: github_document
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
# holi
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<!-- badges: end -->
The goal of holi is to provide web applications for higher order likelihood inference.
## Installation
You can install the development version of holi from [GitHub](https://github.com/) with:
``` r
# install.packages("devtools")
devtools::install_github("mightymetrika/holi")
```
## Example
This is a basic example which shows you how to compare the p-value from stats::glm() and the r* p-value from holi::rstar_glm() when analyzing 'mtcars'. The holi::rstar_glm() function relies on likelihoodAsy::rstar().
```{r example}
library(holi)
# Fit model
rs_linear <- rstar_glm(mpg ~ wt + hp, .data = mtcars, .model = "linear")
# See results from stats::glm()
rs_linear$fit_glm |> summary()
# See r* results
rs_linear$fit_glm |> summary()
```
In this example, the p-value for r* (5.556e-07) is smaller than the p-value for stats::glm() (1.12e-06).
## References
Pierce, D. A., & Bellio, R. (2017). Modern Likelihood-Frequentist Inference. International Statistical Review / Revue Internationale de Statistique, 85(3), 519–541. <doi:10.1111/insr.12232>