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!

Logarithm of Probability Density Function

[![NPM version][npm-image]][npm-url] [![Build Status][test-image]][test-url] [![Coverage Status][coverage-image]][coverage-url]

> Evaluate the natural logarithm of the [probability density function][pdf] (PDF) for a [chi][chi-distribution] distribution.

The [probability density function][pdf] (PDF) for a [chi][chi-distribution] random variable is

Probability density function (PDF) for a chi distribution.

where k is the degrees of freedom and Γ denotes the [gamma][gamma-function] function.

Installation

``bash npm install @stdlib/stats-base-dists-chi-logpdf`

`Usage`

`javascript var logpdf = require( '@stdlib/stats-base-dists-chi-logpdf' );`

#### logpdf( x, k )

Evaluates the natural logarithm of the [probability density function][pdf] (PDF) for a [chi][chi-distribution] distribution with degrees of freedom k.

`javascript var y = logpdf( 0.1, 1.0 ); // returns ~-0.231

y = logpdf( 0.5, 2.0 ); // returns ~-0.818

y = logpdf( -1.0, 4.0 ); // returns -Infinity`

If provided NaN as any argument, the function returns NaN.

`javascript var y = logpdf( NaN, 1.0 ); // returns NaN

y = logpdf( 0.0, NaN ); // returns NaN`

If provided k < 0, the function returns NaN.

`javascript var y = logpdf( 2.0, -2.0 ); // returns NaN`

If provided k = 0, the function evaluates the natural logarithm of the [PDF][pdf] for a [degenerate distribution][degenerate-distribution] centered at 0.

`javascript var y = logpdf( 2.0, 0.0 ); // returns -Infinity

y = logpdf( 0.0, 0.0 ); // returns Infinity`

#### logpdf.factory( k )

Returns a function for evaluating the natural logarithm of the [PDF][pdf] for a [chi][chi-distribution] distribution with degrees of freedom k.

`javascript var mylogPDF = logpdf.factory( 6.0 );

var y = mylogPDF( 3.0 ); // returns ~-1.086

y = mylogPDF( 1.0 ); // returns ~-2.579`

`Examples`

`javascript var uniform = require( '@stdlib/random-array-uniform' ); var logEachMap = require( '@stdlib/console-log-each-map' ); var logpdf = require( '@stdlib/stats-base-dists-chi-logpdf' );

var opts = { 'dtype': 'float64' }; var x = uniform( 20, 0.0, 10.0, opts ); var k = uniform( 20, 0.0, 10.0, opts );

logEachMap( 'x: %0.4f, k: %0.4f, ln(f(x;k)): %0.4f', x, k, logpdf );`

*

`C APIs`

`$3`

`c #include "stdlib/stats/base/dists/chi/logpdf.h"`

#### stdlib_base_dists_chi_logpdf( x, k )

Evaluates the natural logarithm of the [probability density function][pdf] (PDF) for a [chi][chi-distribution] distribution with degrees of freedom k.

`c double out = stdlib_base_dists_chi_logpdf( 2.0, 2.0 ); // returns ~-1.309`

The function accepts the following arguments:

- x: [in] doubleinput value. - k:[in] double degrees of freedom.

`c double stdlib_base_dists_chi_logpdf( const double x, const double k );`

`$3`

`c #include "stdlib/stats/base/dists/chi/logpdf.h" #include #include

static double random_uniform( const double min, const double max ) { double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); return min + ( v*(max-min) ); }

int main( void ) { double x; double k; double y; int i;

for ( i = 0; i < 25; i++ ) { x = random_uniform( 0.0, 10.0 ); k = random_uniform( 0.1, 10.0 ); y = stdlib_base_dists_chi_logpdf( x, k ); printf( "x: %lf, k: %lf, ln(f(x;k)): %lf\n", x, k, y ); } }`

*

`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`

[npm-image]: http://img.shields.io/npm/v/@stdlib/stats-base-dists-chi-logpdf.svg [npm-url]: https://npmjs.org/package/@stdlib/stats-base-dists-chi-logpdf

[test-image]: https://github.com/stdlib-js/stats-base-dists-chi-logpdf/actions/workflows/test.yml/badge.svg?branch=v0.3.1 [test-url]: https://github.com/stdlib-js/stats-base-dists-chi-logpdf/actions/workflows/test.yml?query=branch:v0.3.1

[coverage-image]: https://img.shields.io/codecov/c/github/stdlib-js/stats-base-dists-chi-logpdf/main.svg [coverage-url]: https://codecov.io/github/stdlib-js/stats-base-dists-chi-logpdf?branch=main

[chat-image]: https://img.shields.io/badge/zulip-join_chat-brightgreen.svg [chat-url]: https://stdlib.zulipchat.com

[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-chi-logpdf/tree/deno [deno-readme]: https://github.com/stdlib-js/stats-base-dists-chi-logpdf/blob/deno/README.md [umd-url]: https://github.com/stdlib-js/stats-base-dists-chi-logpdf/tree/umd [umd-readme]: https://github.com/stdlib-js/stats-base-dists-chi-logpdf/blob/umd/README.md [esm-url]: https://github.com/stdlib-js/stats-base-dists-chi-logpdf/tree/esm [esm-readme]: https://github.com/stdlib-js/stats-base-dists-chi-logpdf/blob/esm/README.md [branches-url]: https://github.com/stdlib-js/stats-base-dists-chi-logpdf/blob/main/branches.md

[stdlib-license]: https://raw.githubusercontent.com/stdlib-js/stats-base-dists-chi-logpdf/main/LICENSE

[chi-distribution]: https://en.wikipedia.org/wiki/Chi_distribution

[degenerate-distribution]: https://en.wikipedia.org/wiki/Degenerate_distribution

[gamma-function]: https://en.wikipedia.org/wiki/Gamma_function

[pdf]: https://en.wikipedia.org/wiki/Probability_density_function


  
    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!

`Logarithm of Probability Density Function`

[![NPM version][npm-image]][npm-url] [![Build Status][test-image]][test-url] [![Coverage Status][coverage-image]][coverage-url]

> Evaluate the natural logarithm of the [probability density function][pdf] (PDF) for a [chi][chi-distribution] distribution.

The [probability density function][pdf] (PDF) for a [chi][chi-distribution] random variable is

where k is the degrees of freedom and Γ denotes the [gamma][gamma-function] function.

`Installation`

``bash npm install @stdlib/stats-base-dists-chi-logpdf `

`Usage`

`javascript var logpdf = require( '@stdlib/stats-base-dists-chi-logpdf' ); `

#### logpdf( x, k )

Evaluates the natural logarithm of the [probability density function][pdf] (PDF) for a [chi][chi-distribution] distribution with degrees of freedom k.

`javascript var y = logpdf( 0.1, 1.0 ); // returns ~-0.231

y = logpdf( 0.5, 2.0 ); // returns ~-0.818

y = logpdf( -1.0, 4.0 ); // returns -Infinity `

If provided NaN as any argument, the function returns NaN.

`javascript var y = logpdf( NaN, 1.0 ); // returns NaN

y = logpdf( 0.0, NaN ); // returns NaN `

If provided k < 0, the function returns NaN.

`javascript var y = logpdf( 2.0, -2.0 ); // returns NaN `

If provided k = 0, the function evaluates the natural logarithm of the [PDF][pdf] for a [degenerate distribution][degenerate-distribution] centered at 0.

`javascript var y = logpdf( 2.0, 0.0 ); // returns -Infinity

y = logpdf( 0.0, 0.0 ); // returns Infinity `

#### logpdf.factory( k )

Returns a function for evaluating the natural logarithm of the [PDF][pdf] for a [chi][chi-distribution] distribution with degrees of freedom k.

`javascript var mylogPDF = logpdf.factory( 6.0 );

var y = mylogPDF( 3.0 ); // returns ~-1.086

y = mylogPDF( 1.0 ); // returns ~-2.579 `

`Examples`

`javascript var uniform = require( '@stdlib/random-array-uniform' ); var logEachMap = require( '@stdlib/console-log-each-map' ); var logpdf = require( '@stdlib/stats-base-dists-chi-logpdf' );

var opts = { 'dtype': 'float64' }; var x = uniform( 20, 0.0, 10.0, opts ); var k = uniform( 20, 0.0, 10.0, opts );

logEachMap( 'x: %0.4f, k: %0.4f, ln(f(x;k)): %0.4f', x, k, logpdf ); `

*

`C APIs`

`$3`

`c #include "stdlib/stats/base/dists/chi/logpdf.h" `

#### stdlib_base_dists_chi_logpdf( x, k )

Evaluates the natural logarithm of the [probability density function][pdf] (PDF) for a [chi][chi-distribution] distribution with degrees of freedom k.

`c double out = stdlib_base_dists_chi_logpdf( 2.0, 2.0 ); // returns ~-1.309 `

The function accepts the following arguments:

- x: [in] double input value. - k: [in] double degrees of freedom.

`c double stdlib_base_dists_chi_logpdf( const double x, const double k ); `

`$3`

`c #include "stdlib/stats/base/dists/chi/logpdf.h" #include #include

static double random_uniform( const double min, const double max ) { double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); return min + ( v*(max-min) ); }

int main( void ) { double x; double k; double y; int i;

for ( i = 0; i < 25; i++ ) { x = random_uniform( 0.0, 10.0 ); k = random_uniform( 0.1, 10.0 ); y = stdlib_base_dists_chi_logpdf( x, k ); printf( "x: %lf, k: %lf, ln(f(x;k)): %lf\n", x, k, y ); } } `

*

`Notice`

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`

[npm-image]: http://img.shields.io/npm/v/@stdlib/stats-base-dists-chi-logpdf.svg [npm-url]: https://npmjs.org/package/@stdlib/stats-base-dists-chi-logpdf

[coverage-image]: https://img.shields.io/codecov/c/github/stdlib-js/stats-base-dists-chi-logpdf/main.svg [coverage-url]: https://codecov.io/github/stdlib-js/stats-base-dists-chi-logpdf?branch=main

[chat-image]: https://img.shields.io/badge/zulip-join_chat-brightgreen.svg [chat-url]: https://stdlib.zulipchat.com

[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

[stdlib-license]: https://raw.githubusercontent.com/stdlib-js/stats-base-dists-chi-logpdf/main/LICENSE

[chi-distribution]: https://en.wikipedia.org/wiki/Chi_distribution

[degenerate-distribution]: https://en.wikipedia.org/wiki/Degenerate_distribution

[gamma-function]: https://en.wikipedia.org/wiki/Gamma_function

[pdf]: https://en.wikipedia.org/wiki/Probability_density_function