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@stdlib/stats-base-dists-pareto-type1-logcdf

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  • License Apache-2.0

Natural logarithm of the cumulative distribution function (CDF)for a Pareto (Type I) distribution.

Package Exports

  • @stdlib/stats-base-dists-pareto-type1-logcdf

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Readme

Logarithm of Cumulative Distribution Function

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Evaluate the natural logarithm of the cumulative distribution function for a Pareto (Type I) distribution.

The cumulative distribution function for a Pareto (Type I) random variable is

Cumulative distribution function for a Pareto (Type I) distribution.

and zero otherwise. In the equation, alpha > 0 is the shape parameter and beta > 0 is the scale parameter.

Installation

npm install @stdlib/stats-base-dists-pareto-type1-logcdf

Usage

var logcdf = require( '@stdlib/stats-base-dists-pareto-type1-logcdf' );

logcdf( x, alpha, beta )

Evaluates the natural logarithm of the cumulative distribution function (CDF) for a Pareto (Type I) distribution with parameters alpha (shape parameter) and beta (scale parameter).

var y = logcdf( 2.0, 1.0, 1.0 );
// returns ~-0.693

y = logcdf( 5.0, 2.0, 4.0 );
// returns ~-1.022

y = logcdf( 4.0, 2.0, 2.0 );
// returns ~-0.288

y = logcdf( 1.9, 2.0, 2.0 );
// returns -Infinity

y = logcdf( +Infinity, 4.0, 2.0 );
// returns 0.0

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

var y = logcdf( NaN, 1.0, 1.0 );
// returns NaN

y = logcdf( 0.0, NaN, 1.0 );
// returns NaN

y = logcdf( 0.0, 1.0, NaN );
// returns NaN

If provided alpha <= 0, the function returns NaN.

var y = logcdf( 2.0, -1.0, 0.5 );
// returns NaN

y = logcdf( 2.0, 0.0, 0.5 );
// returns NaN

If provided beta <= 0, the function returns NaN.

var y = logcdf( 2.0, 0.5, -1.0 );
// returns NaN

y = logcdf( 2.0, 0.5, 0.0 );
// returns NaN

logcdf.factory( alpha, beta )

Returns a function for evaluating the natural logarithm of the cumulative distribution function (CDF) of a Pareto (Type I) distribution with parameters alpha (shape parameter) and beta (scale parameter).

var mylogcdf = logcdf.factory( 10.0, 2.0 );
var y = mylogcdf( 3.0 );
// returns ~-0.017

y = mylogcdf( 2.5 );
// returns ~-0.114

Notes

  • In virtually all cases, using the logpdf or logcdf functions is preferable to manually computing the logarithm of the pdf or cdf, respectively, since the latter is prone to overflow and underflow.

Examples

var randu = require( '@stdlib/random-base-randu' );
var logcdf = require( '@stdlib/stats-base-dists-pareto-type1-logcdf' );

var alpha;
var beta;
var x;
var y;
var i;

for ( i = 0; i < 10; i++ ) {
    x = randu() * 8.0;
    alpha = randu() * 5.0;
    beta = randu() * 5.0;
    y = logcdf( x, alpha, beta );
    console.log( 'x: %d, α: %d, β: %d, ln(F(x;α,β)): %d', x.toFixed( 4 ), alpha.toFixed( 4 ), beta.toFixed( 4 ), y.toFixed( 4 ) );
}

Notice

This package is part of 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, see the main project repository.


License

See LICENSE.

Copyright © 2016-2021. The Stdlib Authors.