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# npm

## @stdlib/stats-base-dists-arcsine-mean 0.0.7 • Public • Published

# Mean

Arcsine distribution expected value.

The expected value for an arcsine random variable is

where `a` is the minimum support and `b` is the maximum support.

## Installation

`npm install @stdlib/stats-base-dists-arcsine-mean`

## Usage

`var mean = require( '@stdlib/stats-base-dists-arcsine-mean' );`

#### mean( a, b )

Returns the expected value of an arcsine distribution with parameters `a` (minimum support) and `b` (maximum support).

```var v = mean( 0.0, 1.0 );
// returns 0.5

v = mean( 4.0, 12.0 );
// returns 8.0

v = mean( 2.0, 8.0 );
// returns 5.0```

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

```var v = mean( NaN, 2.0 );
// returns NaN

v = mean( 2.0, NaN );
// returns NaN```

If provided `a >= b`, the function returns `NaN`.

```var y = mean( 3.0, 2.0 );
// returns NaN

y = mean( 3.0, 3.0 );
// returns NaN```

## Examples

```var randu = require( '@stdlib/random-base-randu' );
var mean = require( '@stdlib/stats-base-dists-arcsine-mean' );

var a;
var b;
var v;
var i;

for ( i = 0; i < 10; i++ ) {
a = ( randu()*10.0 );
b = ( randu()*10.0 ) + a;
v = mean( a, b );
console.log( 'a: %d, b: %d, E(X;a,b): %d', a.toFixed( 4 ), b.toFixed( 4 ), v.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.

#### Community ### Install

`npm i @stdlib/stats-base-dists-arcsine-mean`

stdlib.io

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0.0.7