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@stdlib/stats

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Standard library statistical functions.

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<!-- @license Apache-2.0 Copyright (c) 2018 The Stdlib Authors. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. --> # Probability Density Function > [Inverse gamma][inverse-gamma] distribution probability density function (PDF). <section class="intro"> The [probability density function][pdf] (PDF) for an [inverse gamma][inverse-gamma] random variable is <!-- <equation class="equation" label="eq:invgamma_pdf" align="center" raw="{\displaystyle f(x;\alpha ,\beta )={\frac {\beta ^{\alpha }}{\Gamma (\alpha )}}x^{-\alpha -1}\exp \left(-{\frac {\beta }{x}}\right)}" alt="Probability density function (PDF) for an inverse gamma distribution."> --> <div class="equation" align="center" data-raw-text="{\displaystyle f(x;\alpha ,\beta )={\frac {\beta ^{\alpha }}{\Gamma (\alpha )}}x^{-\alpha -1}\exp \left(-{\frac {\beta }{x}}\right)}" data-equation="eq:invgamma_pdf"> <img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@591cf9d5c3a0cd3c1ceec961e5c49d73a68374cb/lib/node_modules/@stdlib/stats/base/dists/invgamma/pdf/docs/img/equation_invgamma_pdf.svg" alt="Probability density function (PDF) for an inverse gamma distribution."> <br> </div> <!-- </equation> --> where `alpha > 0` is the shape parameter and `beta > 0` is the scale parameter. </section> <!-- /.intro --> <section class="usage"> ## Usage ```javascript var pdf = require( '@stdlib/stats/base/dists/invgamma/pdf' ); ``` #### pdf( x, alpha, beta ) Evaluates the [probability density function][pdf] (PDF) for an [inverse gamma][inverse-gamma] distribution with parameters `alpha` (shape parameter) and `beta` (rate parameter). ```javascript var y = pdf( 2.0, 0.5, 1.0 ); // returns ~0.121 y = pdf( 0.2, 1.0, 1.0 ); // returns ~0.168 y = pdf( -1.0, 4.0, 2.0 ); // returns 0.0 ``` If provided `NaN` as any argument, the function returns `NaN`. ```javascript var y = pdf( NaN, 1.0, 1.0 ); // returns NaN y = pdf( 0.0, NaN, 1.0 ); // returns NaN y = pdf( 0.0, 1.0, NaN ); // returns NaN ``` If provided `alpha <= 0`, the function returns `NaN`. ```javascript var y = pdf( 2.0, 0.0, 1.0 ); // returns NaN y = pdf( 2.0, -0.5, 1.0 ); // returns NaN ``` If provided `beta <= 0`, the function returns `NaN`. ```javascript var y = pdf( 2.0, 1.0, 0.0 ); // returns NaN y = pdf( 2.0, 1.0, -1.0 ); // returns NaN ``` #### pdf.factory( alpha, beta ) Returns a `function` for evaluating the [PDF][pdf] of an [inverse gamma][inverse-gamma] distribution with parameters `alpha` (shape parameter) and `beta` (rate parameter). ```javascript var myPDF = pdf.factory( 6.0, 7.0 ); var y = myPDF( 2.0 ); // returns ~0.231 ``` </section> <!-- /.usage --> <section class="examples"> ## Examples <!-- eslint no-undef: "error" --> ```javascript var randu = require( '@stdlib/random/base/randu' ); var pdf = require( '@stdlib/stats/base/dists/invgamma/pdf' ); var alpha; var beta; var x; var y; var i; for ( i = 0; i < 10; i++ ) { x = randu() * 2.0; alpha = randu() * 5.0; beta = randu() * 5.0; y = pdf( x, alpha, beta ); console.log( 'x: %d, α: %d, β: %d, f(x;α,β): %d', x.toFixed( 4 ), alpha.toFixed( 4 ), beta.toFixed( 4 ), y.toFixed( 4 ) ); } ``` </section> <!-- /.examples --> <!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. --> <section class="related"> </section> <!-- /.related --> <!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. --> <section class="links"> [inverse-gamma]: https://en.wikipedia.org/wiki/Inverse-gamma_distribution [pdf]: https://en.wikipedia.org/wiki/Probability_density_function </section> <!-- /.links -->