-
Notifications
You must be signed in to change notification settings - Fork 0
/
README.Rmd
68 lines (45 loc) · 1.54 KB
/
README.Rmd
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
---
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%"
)
```
# causnet
<!-- badges: start -->
[![Codecov test coverage](https://codecov.io/gh/USCbiostats/causnet/branch/master/graph/badge.svg)](https://codecov.io/gh/USCbiostats/causnet?branch=master)
[![R build status](https://github.com/USCbiostats/causnet/workflows/R-CMD-check/badge.svg)](https://github.com/USCbiostats/causnet/actions)
<!-- badges: end -->
The goal of causnet is to find a globally optimal causal network given some data.
## Installation
You can install the development version from GitHub with:
```{r installation, eval=FALSE}
require("devtools")
install_github("USCbiostats/causnet")
```
~You can install the released version of causnet from [CRAN](https://CRAN.R-project.org) with:~
``` r
install.packages("causnet")
```
## Example
```{r}
library(causnet)
# simulate data
set.seed(1234)
mydata <- simdat(n_var = 5)
# causnet results
links.s <- causnet(mydata)
links.s
```
### using BGE scoring function
To use he a BGE scoring function simply pass thr `score_bge()` to the `score_fun` argument.
```{r}
causnet(mydata, score_fun = score_bge)
```
## Code of Conduct
Please note that the causnet project is released with a [Contributor Code of Conduct](https://contributor-covenant.org/version/1/0/0/CODE_OF_CONDUCT.html). By contributing to this project, you agree to abide by its terms.