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Stdlib Authors","url":"https://github.com/stdlib-js/stdlib/graphs/contributors"},"license":"Apache-2.0","homepage":"https://stdlib.io","keywords":["stdlib","stdmath","statistics","stats","distribution","dist","object","class","constructor","ctor","probability","prob","chi","squared","chisquare","chisquared","chi-squared","cdf","pdf","quantile","properties","props","univariate","continuous"],"repository":{"type":"git","url":"git://github.com/stdlib-js/stats-base-dists-chisquare-ctor.git"},"description":"Chi-squared distribution constructor.","contributors":[{"name":"The Stdlib Authors","url":"https://github.com/stdlib-js/stdlib/graphs/contributors"}],"maintainers":[{"name":"stdlib-bot","email":"kgryte+stdlibbot@gmail.com"},{"name":"kgryte","email":"kgryte@gmail.com"},{"name":"planeshifter","email":"pgb@andrew.cmu.edu"},{"name":"rreusser","email":"rsreusser@gmail.com"}],"readme":"<!--\n\n@license Apache-2.0\n\nCopyright (c) 2018 The Stdlib Authors.\n\nLicensed under the Apache License, Version 2.0 (the \"License\");\nyou may not use this file except in compliance with the License.\nYou may obtain a copy of the License at\n\n   http://www.apache.org/licenses/LICENSE-2.0\n\nUnless required by applicable law or agreed to in writing, software\ndistributed under the License is distributed on an \"AS IS\" BASIS,\nWITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\nSee the License for the specific language governing permissions and\nlimitations under the License.\n\n-->\n\n\n<details>\n  <summary>\n    About stdlib...\n  </summary>\n  <p>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.</p>\n  <p>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.</p>\n  <p>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.</p>\n  <p>To join us in bringing numerical computing to the web, get started by checking us out on <a href=\"https://github.com/stdlib-js/stdlib\">GitHub</a>, and please consider <a href=\"https://opencollective.com/stdlib\">financially supporting stdlib</a>. We greatly appreciate your continued support!</p>\n</details>\n\n# ChiSquare\n\n[![NPM version][npm-image]][npm-url] [![Build Status][test-image]][test-url] [![Coverage Status][coverage-image]][coverage-url] <!-- [![dependencies][dependencies-image]][dependencies-url] -->\n\n> Chi-squared distribution constructor.\n\n<!-- Section to include introductory text. Make sure to keep an empty line after the intro `section` element and another before the `/section` close. -->\n\n<section class=\"intro\">\n\n</section>\n\n<!-- /.intro -->\n\n<!-- Package usage documentation. -->\n\n<section class=\"installation\">\n\n## Installation\n\n```bash\nnpm install @stdlib/stats-base-dists-chisquare-ctor\n```\n\n</section>\n\n<section class=\"usage\">\n\n## Usage\n\n```javascript\nvar ChiSquare = require( '@stdlib/stats-base-dists-chisquare-ctor' );\n```\n\n#### ChiSquare( \\[k] )\n\nReturns an [chi-squared][chisquare-distribution] distribution object.\n\n```javascript\nvar chisquare = new ChiSquare();\n\nvar mu = chisquare.mean;\n// returns 1.0\n```\n\nBy default, `k = 1.0`. To create a distribution having a different degrees of freedom `k`, provide a parameter value.\n\n```javascript\nvar chisquare = new ChiSquare( 4.0 );\n\nvar mu = chisquare.mean;\n// returns 4.0\n```\n\n* * *\n\n## chisquare\n\nA [chi-squared][chisquare-distribution] distribution object has the following properties and methods...\n\n### Writable Properties\n\n#### chisquare.k\n\nRate parameter of the distribution. `k` **must** be a positive number.\n\n```javascript\nvar chisquare = new ChiSquare( 2.0 );\n\nvar k = chisquare.k;\n// returns 2.0\n\nchisquare.k = 3.0;\n\nk = chisquare.k;\n// returns 3.0\n```\n\n* * *\n\n### Computed Properties\n\n#### ChiSquare.prototype.entropy\n\nReturns the [differential entropy][entropy].\n\n```javascript\nvar chisquare = new ChiSquare( 4.0 );\n\nvar entropy = chisquare.entropy;\n// returns ~2.27\n```\n\n#### ChiSquare.prototype.kurtosis\n\nReturns the [excess kurtosis][kurtosis].\n\n```javascript\nvar chisquare = new ChiSquare( 4.0 );\n\nvar kurtosis = chisquare.kurtosis;\n// returns 3.0\n```\n\n#### ChiSquare.prototype.mean\n\nReturns the [expected value][expected-value].\n\n```javascript\nvar chisquare = new ChiSquare( 4.0 );\n\nvar mu = chisquare.mean;\n// returns 4.0\n```\n\n#### ChiSquare.prototype.median\n\nReturns the [median][median].\n\n```javascript\nvar chisquare = new ChiSquare( 4.0 );\n\nvar median = chisquare.median;\n// returns ~3.357\n```\n\n#### ChiSquare.prototype.mode\n\nReturns the [mode][mode].\n\n```javascript\nvar chisquare = new ChiSquare( 4.0 );\n\nvar mode = chisquare.mode;\n// returns 2.0\n```\n\n#### ChiSquare.prototype.skewness\n\nReturns the [skewness][skewness].\n\n```javascript\nvar chisquare = new ChiSquare( 4.0 );\n\nvar skewness = chisquare.skewness;\n// returns ~1.414\n```\n\n#### ChiSquare.prototype.stdev\n\nReturns the [standard deviation][standard-deviation].\n\n```javascript\nvar chisquare = new ChiSquare( 4.0 );\n\nvar s = chisquare.stdev;\n// returns ~2.828\n```\n\n#### ChiSquare.prototype.variance\n\nReturns the [variance][variance].\n\n```javascript\nvar chisquare = new ChiSquare( 4.0 );\n\nvar s2 = chisquare.variance;\n// returns 8.0\n```\n\n* * *\n\n### Methods\n\n#### ChiSquare.prototype.cdf( x )\n\nEvaluates the [cumulative distribution function][cdf] (CDF).\n\n```javascript\nvar chisquare = new ChiSquare( 2.0 );\n\nvar y = chisquare.cdf( 0.5 );\n// returns ~0.221\n```\n\n#### ChiSquare.prototype.mgf( t )\n\nEvaluates the [moment-generating function][mgf] (MGF).\n\n```javascript\nvar chisquare = new ChiSquare( 2.0 );\n\nvar y = chisquare.mgf( 0.2 );\n// returns ~1.667\n```\n\n#### ChiSquare.prototype.pdf( x )\n\nEvaluates the [probability density function][pdf] (PDF).\n\n```javascript\nvar chisquare = new ChiSquare( 2.0 );\n\nvar y = chisquare.pdf( 0.8 );\n// returns ~0.335\n```\n\n#### ChiSquare.prototype.quantile( p )\n\nEvaluates the [quantile function][quantile-function] at probability `p`.\n\n```javascript\nvar chisquare = new ChiSquare( 2.0 );\n\nvar y = chisquare.quantile( 0.5 );\n// returns ~1.386\n\ny = chisquare.quantile( 1.9 );\n// returns NaN\n```\n\n</section>\n\n<!-- /.usage -->\n\n<!-- Package usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->\n\n<section class=\"notes\">\n\n</section>\n\n<!-- /.notes -->\n\n<!-- Package usage examples. -->\n\n* * *\n\n<section class=\"examples\">\n\n## Examples\n\n<!-- eslint no-undef: \"error\" -->\n\n```javascript\nvar ChiSquare = require( '@stdlib/stats-base-dists-chisquare-ctor' );\n\nvar chisquare = new ChiSquare( 2.0 );\n\nvar mu = chisquare.mean;\n// returns 2.0\n\nvar mode = chisquare.mode;\n// returns 0.0\n\nvar s2 = chisquare.variance;\n// returns 4.0\n\nvar y = chisquare.cdf( 0.8 );\n// returns ~0.33\n```\n\n</section>\n\n<!-- /.examples -->\n\n<!-- Section to include cited references. If references are included, add a horizontal rule *before* the section. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->\n\n<section class=\"references\">\n\n</section>\n\n<!-- /.references -->\n\n<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->\n\n<section class=\"related\">\n\n</section>\n\n<!-- /.related -->\n\n<!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->\n\n\n<section class=\"main-repo\" >\n\n* * *\n\n## Notice\n\nThis 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.\n\nFor 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].\n\n#### Community\n\n[![Chat][chat-image]][chat-url]\n\n---\n\n## License\n\nSee [LICENSE][stdlib-license].\n\n\n## Copyright\n\nCopyright &copy; 2016-2026. The Stdlib [Authors][stdlib-authors].\n\n</section>\n\n<!-- /.stdlib -->\n\n<!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->\n\n<section class=\"links\">\n\n[npm-image]: http://img.shields.io/npm/v/@stdlib/stats-base-dists-chisquare-ctor.svg\n[npm-url]: https://npmjs.org/package/@stdlib/stats-base-dists-chisquare-ctor\n\n[test-image]: https://github.com/stdlib-js/stats-base-dists-chisquare-ctor/actions/workflows/test.yml/badge.svg?branch=v0.2.3\n[test-url]: https://github.com/stdlib-js/stats-base-dists-chisquare-ctor/actions/workflows/test.yml?query=branch:v0.2.3\n\n[coverage-image]: https://img.shields.io/codecov/c/github/stdlib-js/stats-base-dists-chisquare-ctor/main.svg\n[coverage-url]: https://codecov.io/github/stdlib-js/stats-base-dists-chisquare-ctor?branch=main\n\n<!--\n\n[dependencies-image]: https://img.shields.io/david/stdlib-js/stats-base-dists-chisquare-ctor.svg\n[dependencies-url]: https://david-dm.org/stdlib-js/stats-base-dists-chisquare-ctor/main\n\n-->\n\n[chat-image]: https://img.shields.io/badge/zulip-join_chat-brightgreen.svg\n[chat-url]: https://stdlib.zulipchat.com\n\n[stdlib]: https://github.com/stdlib-js/stdlib\n\n[stdlib-authors]: https://github.com/stdlib-js/stdlib/graphs/contributors\n\n[umd]: https://github.com/umdjs/umd\n[es-module]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Modules\n\n[deno-url]: https://github.com/stdlib-js/stats-base-dists-chisquare-ctor/tree/deno\n[deno-readme]: https://github.com/stdlib-js/stats-base-dists-chisquare-ctor/blob/deno/README.md\n[umd-url]: https://github.com/stdlib-js/stats-base-dists-chisquare-ctor/tree/umd\n[umd-readme]: https://github.com/stdlib-js/stats-base-dists-chisquare-ctor/blob/umd/README.md\n[esm-url]: https://github.com/stdlib-js/stats-base-dists-chisquare-ctor/tree/esm\n[esm-readme]: https://github.com/stdlib-js/stats-base-dists-chisquare-ctor/blob/esm/README.md\n[branches-url]: https://github.com/stdlib-js/stats-base-dists-chisquare-ctor/blob/main/branches.md\n\n[stdlib-license]: https://raw.githubusercontent.com/stdlib-js/stats-base-dists-chisquare-ctor/main/LICENSE\n\n[chisquare-distribution]: https://en.wikipedia.org/wiki/Chi-squared_distribution\n\n[cdf]: https://en.wikipedia.org/wiki/Cumulative_distribution_function\n\n[mgf]: https://en.wikipedia.org/wiki/Moment-generating_function\n\n[pdf]: https://en.wikipedia.org/wiki/Probability_density_function\n\n[quantile-function]: https://en.wikipedia.org/wiki/Quantile_function\n\n[entropy]: https://en.wikipedia.org/wiki/Entropy_%28information_theory%29\n\n[expected-value]: https://en.wikipedia.org/wiki/Expected_value\n\n[kurtosis]: https://en.wikipedia.org/wiki/Kurtosis\n\n[median]: https://en.wikipedia.org/wiki/Median\n\n[mode]: https://en.wikipedia.org/wiki/Mode_%28statistics%29\n\n[skewness]: https://en.wikipedia.org/wiki/Skewness\n\n[standard-deviation]: https://en.wikipedia.org/wiki/Standard_deviation\n\n[variance]: https://en.wikipedia.org/wiki/Variance\n\n</section>\n\n<!-- /.links -->\n","readmeFilename":"README.md"}