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https://github.com/stdlib-js/stats-base-dists-t
Student's t distribution.
https://github.com/stdlib-js/stats-base-dists-t
continuous dist distribution javascript lib library node node-js nodejs probability standard statistics stats stdlib t univariate
Last synced: about 1 month ago
JSON representation
Student's t distribution.
- Host: GitHub
- URL: https://github.com/stdlib-js/stats-base-dists-t
- Owner: stdlib-js
- License: apache-2.0
- Created: 2021-06-15T17:42:58.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2024-11-01T11:56:33.000Z (about 2 months ago)
- Last Synced: 2024-11-11T03:32:34.364Z (about 1 month ago)
- Topics: continuous, dist, distribution, javascript, lib, library, node, node-js, nodejs, probability, standard, statistics, stats, stdlib, t, univariate
- Language: JavaScript
- Homepage: https://github.com/stdlib-js/stdlib
- Size: 2.93 MB
- Stars: 2
- Watchers: 3
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
- Citation: CITATION.cff
- Security: SECURITY.md
Awesome Lists containing this project
README
About stdlib...
We believe in a future in which the web is a preferred environment for numerical computation. To help realize this future, we've built stdlib. stdlib is a standard library, with an emphasis on numerical and scientific computation, written in JavaScript (and C) for execution in browsers and in Node.js.
The library is fully decomposable, being architected in such a way that you can swap out and mix and match APIs and functionality to cater to your exact preferences and use cases.
When you use stdlib, you can be absolutely certain that you are using the most thorough, rigorous, well-written, studied, documented, tested, measured, and high-quality code out there.
To join us in bringing numerical computing to the web, get started by checking us out on GitHub, and please consider financially supporting stdlib. We greatly appreciate your continued support!
# Student's T
[![NPM version][npm-image]][npm-url] [![Build Status][test-image]][test-url] [![Coverage Status][coverage-image]][coverage-url]
> Student's t distribution.
## Installation
```bash
npm install @stdlib/stats-base-dists-t
```
Alternatively,
- To load the package in a website via a `script` tag without installation and bundlers, use the [ES Module][es-module] available on the [`esm`][esm-url] branch (see [README][esm-readme]).
- If you are using Deno, visit the [`deno`][deno-url] branch (see [README][deno-readme] for usage intructions).
- For use in Observable, or in browser/node environments, use the [Universal Module Definition (UMD)][umd] build available on the [`umd`][umd-url] branch (see [README][umd-readme]).
The [branches.md][branches-url] file summarizes the available branches and displays a diagram illustrating their relationships.
To view installation and usage instructions specific to each branch build, be sure to explicitly navigate to the respective README files on each branch, as linked to above.
## Usage
```javascript
var t = require( '@stdlib/stats-base-dists-t' );
```
#### t
Student's t distribution.
```javascript
var dist = t;
// returns {...}
```
The namespace contains the following distribution functions:
- [`cdf( x, v )`][@stdlib/stats/base/dists/t/cdf]: Student's t distribution cumulative distribution function (CDF).
- [`logcdf( x, v )`][@stdlib/stats/base/dists/t/logcdf]: evaluate the natural logarithm of the cumulative distribution function (CDF) for a Student's t distribution.
- [`logpdf( x, v )`][@stdlib/stats/base/dists/t/logpdf]: evaluate the natural logarithm of the probability density function (PDF) for a Student's t distribution.
- [`pdf( x, v )`][@stdlib/stats/base/dists/t/pdf]: Student's t distribution probability density function (PDF).
- [`quantile( p, v )`][@stdlib/stats/base/dists/t/quantile]: Student's t distribution quantile function.
The namespace contains the following functions for calculating distribution properties:
- [`entropy( v )`][@stdlib/stats/base/dists/t/entropy]: Student's t distribution differential entropy.
- [`kurtosis( v )`][@stdlib/stats/base/dists/t/kurtosis]: Student's t distribution excess kurtosis.
- [`mean( v )`][@stdlib/stats/base/dists/t/mean]: Student's t distribution expected value.
- [`median( v )`][@stdlib/stats/base/dists/t/median]: Student's t distribution median.
- [`mode( v )`][@stdlib/stats/base/dists/t/mode]: Student's t distribution mode.
- [`skewness( v )`][@stdlib/stats/base/dists/t/skewness]: Student's t distribution skewness.
- [`stdev( v )`][@stdlib/stats/base/dists/t/stdev]: Student's t distribution variance.
- [`variance( v )`][@stdlib/stats/base/dists/t/variance]: Student's t distribution variance.
The namespace contains a constructor function for creating a [Student's t][t-distribution] distribution object.
- [`T( [v] )`][@stdlib/stats/base/dists/t/ctor]: Student's t distribution constructor.
```javascript
var T = require( '@stdlib/stats-base-dists-t' ).T;
var dist = new T( 2.0 );
var y = dist.cdf( 0.5 );
// returns ~0.667
```
## Examples
```javascript
var t = require( '@stdlib/stats-base-dists-t' );
var dof = 3;
var x = 1.5;
// Evaluate the probability density function (PDF) at a specific value:
var res = t.pdf( x, dof );
console.log( 'PDF at x = ' + x + ': ' + res );
// Evaluate the cumulative distribution function (CDF) at a specific value:
res = t.cdf( x, dof );
console.log( 'CDF at x = ' + x + ': ' + res );
// Get the mean and variance of the t distribution:
var mu = t.mean( dof );
var v = t.variance( dof );
console.log( 'Mean: ' + mu + ', Variance: ' + v );
```
* * *
## Notice
This package is part of [stdlib][stdlib], a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more.
For more information on the project, filing bug reports and feature requests, and guidance on how to develop [stdlib][stdlib], see the main project [repository][stdlib].
#### Community
[![Chat][chat-image]][chat-url]
---
## License
See [LICENSE][stdlib-license].
## Copyright
Copyright © 2016-2024. The Stdlib [Authors][stdlib-authors].
[npm-image]: http://img.shields.io/npm/v/@stdlib/stats-base-dists-t.svg
[npm-url]: https://npmjs.org/package/@stdlib/stats-base-dists-t
[test-image]: https://github.com/stdlib-js/stats-base-dists-t/actions/workflows/test.yml/badge.svg?branch=main
[test-url]: https://github.com/stdlib-js/stats-base-dists-t/actions/workflows/test.yml?query=branch:main
[coverage-image]: https://img.shields.io/codecov/c/github/stdlib-js/stats-base-dists-t/main.svg
[coverage-url]: https://codecov.io/github/stdlib-js/stats-base-dists-t?branch=main
[chat-image]: https://img.shields.io/gitter/room/stdlib-js/stdlib.svg
[chat-url]: https://app.gitter.im/#/room/#stdlib-js_stdlib:gitter.im
[stdlib]: https://github.com/stdlib-js/stdlib
[stdlib-authors]: https://github.com/stdlib-js/stdlib/graphs/contributors
[umd]: https://github.com/umdjs/umd
[es-module]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Modules
[deno-url]: https://github.com/stdlib-js/stats-base-dists-t/tree/deno
[deno-readme]: https://github.com/stdlib-js/stats-base-dists-t/blob/deno/README.md
[umd-url]: https://github.com/stdlib-js/stats-base-dists-t/tree/umd
[umd-readme]: https://github.com/stdlib-js/stats-base-dists-t/blob/umd/README.md
[esm-url]: https://github.com/stdlib-js/stats-base-dists-t/tree/esm
[esm-readme]: https://github.com/stdlib-js/stats-base-dists-t/blob/esm/README.md
[branches-url]: https://github.com/stdlib-js/stats-base-dists-t/blob/main/branches.md
[stdlib-license]: https://raw.githubusercontent.com/stdlib-js/stats-base-dists-t/main/LICENSE
[t-distribution]: https://en.wikipedia.org/wiki/Student%27s_t-distribution
[@stdlib/stats/base/dists/t/ctor]: https://github.com/stdlib-js/stats-base-dists-t-ctor
[@stdlib/stats/base/dists/t/entropy]: https://github.com/stdlib-js/stats-base-dists-t-entropy
[@stdlib/stats/base/dists/t/kurtosis]: https://github.com/stdlib-js/stats-base-dists-t-kurtosis
[@stdlib/stats/base/dists/t/mean]: https://github.com/stdlib-js/stats-base-dists-t-mean
[@stdlib/stats/base/dists/t/median]: https://github.com/stdlib-js/stats-base-dists-t-median
[@stdlib/stats/base/dists/t/mode]: https://github.com/stdlib-js/stats-base-dists-t-mode
[@stdlib/stats/base/dists/t/skewness]: https://github.com/stdlib-js/stats-base-dists-t-skewness
[@stdlib/stats/base/dists/t/stdev]: https://github.com/stdlib-js/stats-base-dists-t-stdev
[@stdlib/stats/base/dists/t/variance]: https://github.com/stdlib-js/stats-base-dists-t-variance
[@stdlib/stats/base/dists/t/cdf]: https://github.com/stdlib-js/stats-base-dists-t-cdf
[@stdlib/stats/base/dists/t/logcdf]: https://github.com/stdlib-js/stats-base-dists-t-logcdf
[@stdlib/stats/base/dists/t/logpdf]: https://github.com/stdlib-js/stats-base-dists-t-logpdf
[@stdlib/stats/base/dists/t/pdf]: https://github.com/stdlib-js/stats-base-dists-t-pdf
[@stdlib/stats/base/dists/t/quantile]: https://github.com/stdlib-js/stats-base-dists-t-quantile