https://github.com/jaysonmulwa/probabilis
NPM Package - A collection of Probability distribution functions.
https://github.com/jaysonmulwa/probabilis
node-module probability
Last synced: 5 months ago
JSON representation
NPM Package - A collection of Probability distribution functions.
- Host: GitHub
- URL: https://github.com/jaysonmulwa/probabilis
- Owner: jaysonmulwa
- License: mit
- Created: 2020-05-26T19:25:51.000Z (about 6 years ago)
- Default Branch: master
- Last Pushed: 2020-08-18T12:10:16.000Z (almost 6 years ago)
- Last Synced: 2025-08-16T15:53:16.231Z (10 months ago)
- Topics: node-module, probability
- Language: JavaScript
- Homepage: https://www.npmjs.com/package/probabilis
- Size: 62.5 KB
- Stars: 1
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
Awesome Lists containing this project
README
[](https://github.com/jaysonmulwa/probabilis/)
[](https://www.codefactor.io/repository/github/jaysonmulwa/probabilis)
An open-source collection of Probability distribution functions.
## Installation
This is a [Node.js](https://nodejs.org/en/) module available through the
[npm registry](https://www.npmjs.com/).
Before installing, [download and install Node.js](https://nodejs.org/en/download/).
Node.js 0.10 or higher is required.
If this is a brand new project, make sure to create a `package.json` first with
the [`npm init` command](https://docs.npmjs.com/creating-a-package-json-file).
Installation is done using the
[`npm install` command](https://docs.npmjs.com/getting-started/installing-npm-packages-locally):
```bash
$ npm install probabilis
```
## Features / Distributions included
Probabilis contains a wide-range of distribution functions:
* Binomial Distribution
* Negative Binomial Distribution
* Bernoulli Distribution
* Geometric Distribution
* Exponential Distribution
* Poisson Distribution
Even more to come!
## Usage Example
```js
const probabilis = require('probabilis')
let result = probabilis.Binomial(2, 1, 0.5)
//let result = probabilis.NegativeBinomial(2, 1, 0.5) - Another Example
console.log(result)
```
## Full API
### Reference
* n - Number of occurences
* k - kth occurence
* p - Probability of 1 occurence (Probability of success in other distributions like Bernoulli's)
* s - Discrete value (0 - failure, 1 - success)
* x - A discrete value
* gamma - Mean value
### 1. Binomial Distribution
```js
Binomial(n, k, p)
```
### 2. Negative Binomial Distribution
```js
NegativeBinomial(n, k, p)
```
### 3. Bernoulli Distribution
```js
Bernoulli(p, s)
```
### 4. Geometric Distribution
```js
Geometric(x, p)
```
### 5. Exponential Distribution
```js
Exponential(gamma, x)
```
### 6. Poisson Distribution
```js
Poisson(gamma, x)
```
## License
[MIT](LICENSE)