https://github.com/boyiguo1/mote.rf
Multivariate Outcome Treatment Effect Random Forest
https://github.com/boyiguo1/mote.rf
heterogeneity multivariate random-forest treatment-effects
Last synced: 7 months ago
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Multivariate Outcome Treatment Effect Random Forest
- Host: GitHub
- URL: https://github.com/boyiguo1/mote.rf
- Owner: boyiguo1
- License: other
- Created: 2020-10-19T22:02:25.000Z (almost 5 years ago)
- Default Branch: master
- Last Pushed: 2023-01-23T14:55:50.000Z (over 2 years ago)
- Last Synced: 2025-03-15T02:46:46.855Z (7 months ago)
- Topics: heterogeneity, multivariate, random-forest, treatment-effects
- Language: C++
- Homepage: https://boyiguo1.github.io/MOTE.RF
- Size: 210 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.Rmd
- License: LICENSE
Awesome Lists containing this project
README
---
output: github_document
---
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
# MOTE.RF
[](https://github.com/boyiguo1/MOTE.RF/actions)
[](https://lifecycle.r-lib.org/articles/stages.html#experimental)
The goal of MOTE.RF is to ...
## Installation
You can install the released version of MOTE.RF from [CRAN](https://CRAN.R-project.org) with:
``` r
install.packages("MOTE.RF")
```
And the development version from [GitHub](https://github.com/) with:
``` r
# install.packages("devtools")
devtools::install_github("boyiguo1/MOTE.RF")
```
## Example
This is a basic example which shows you how to solve a common problem:
```{r example}
library(MOTE.RF)
## basic example code
```
What is special about using `README.Rmd` instead of just `README.md`? You can include R chunks like so:
```{r cars}
summary(cars)
```
You'll still need to render `README.Rmd` regularly, to keep `README.md` up-to-date. `devtools::build_readme()` is handy for this. You could also use GitHub Actions to re-render `README.Rmd` every time you push. An example workflow can be found here: .
You can also embed plots, for example:
```{r pressure, echo = FALSE}
plot(pressure)
```
In that case, don't forget to commit and push the resulting figure files, so they display on GitHub and CRAN.