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

Pareto (Type I)

Pareto (Type I) distribution.

Installation

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

Usage

var pareto1 = require( '@stdlib/stats-base-dists-pareto-type1' );

pareto1

Pareto (Type I) distribution.

var dist = pareto1;
// returns {...}

The namespace contains the following distribution functions:

cdf( x, alpha, beta ): Pareto (Type I) distribution cumulative distribution function.
logcdf( x, alpha, beta ): evaluate the natural logarithm of the cumulative distribution function for a Pareto (Type I) distribution.
logpdf( x, alpha, beta ): evaluate the natural logarithm of the probability density function (PDF) for a Pareto (Type I) distribution.
pdf( x, alpha, beta ): Pareto (Type I) distribution probability density function (PDF).
quantile( p, alpha, beta ): Pareto (Type I) distribution quantile function.

The namespace contains the following functions for calculating distribution properties:

entropy( alpha, beta ): Pareto (Type I) distribution differential entropy.
kurtosis( alpha, beta ): Pareto (Type I) distribution excess kurtosis.
mean( alpha, beta ): Pareto (Type I) distribution expected value.
median( alpha, beta ): Pareto (Type I) distribution median.
mode( alpha, beta ): Pareto (Type I) distribution mode.
skewness( alpha, beta ): Pareto (Type I) distribution skewness.
stdev( alpha, beta ): Pareto (Type I) distribution standard deviation.
variance( alpha, beta ): Pareto (Type I) distribution variance.

The namespace contains a constructor function for creating a Pareto (Type I) distribution object.

Pareto1( [alpha, beta] ): Pareto (Type I) distribution constructor.

var Pareto1 = require( '@stdlib/stats-base-dists-pareto-type1' ).Pareto1;

var dist = new Pareto1( 2.0, 4.0 );

var y = dist.cdf( 3.5 );
// returns 0.0

Examples

var objectKeys = require( '@stdlib/utils-keys' );
var pareto1 = require( '@stdlib/stats-base-dists-pareto-type1' );

console.log( objectKeys( pareto1 ) );

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.