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CHANGELOG.md

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<!-- /.package -->
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<section class="package" id="stats-base-dists-betaprime-variance-unreleased">
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#### [@stdlib/stats/base/dists/betaprime/variance](https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dists/betaprime/variance)
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<details>
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<section class="features">
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##### Features
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- [`c77a433`](https://github.com/stdlib-js/stdlib/commit/c77a433d6e33ad5f4879d32211d8cfdb4e5fa2c6) - add C implementation for `stats/base/dists/betaprime/variance` [(#3460)](https://github.com/stdlib-js/stdlib/pull/3460)
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</section>
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<!-- /.features -->
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<section class="issues">
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##### Closed Issues
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This release closes the following issue:
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[#3447](https://github.com/stdlib-js/stdlib/issues/3447)
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</section>
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<!-- /.issues -->
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</details>
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</section>
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<!-- /.package -->
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<section class="package" id="stats-base-dists-chisquare-unreleased">
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#### [@stdlib/stats/base/dists/chisquare](https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dists/chisquare)
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### Closed Issues
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A total of 14 issues were closed in this release:
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A total of 15 issues were closed in this release:
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[#1619](https://github.com/stdlib-js/stdlib/issues/1619), [#1632](https://github.com/stdlib-js/stdlib/issues/1632), [#1633](https://github.com/stdlib-js/stdlib/issues/1633), [#3236](https://github.com/stdlib-js/stdlib/issues/3236), [#3237](https://github.com/stdlib-js/stdlib/issues/3237), [#3238](https://github.com/stdlib-js/stdlib/issues/3238), [#3378](https://github.com/stdlib-js/stdlib/issues/3378), [#3384](https://github.com/stdlib-js/stdlib/issues/3384), [#3385](https://github.com/stdlib-js/stdlib/issues/3385), [#3401](https://github.com/stdlib-js/stdlib/issues/3401), [#3414](https://github.com/stdlib-js/stdlib/issues/3414), [#3445](https://github.com/stdlib-js/stdlib/issues/3445), [#3446](https://github.com/stdlib-js/stdlib/issues/3446), [#3671](https://github.com/stdlib-js/stdlib/issues/3671)
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[#1619](https://github.com/stdlib-js/stdlib/issues/1619), [#1632](https://github.com/stdlib-js/stdlib/issues/1632), [#1633](https://github.com/stdlib-js/stdlib/issues/1633), [#3236](https://github.com/stdlib-js/stdlib/issues/3236), [#3237](https://github.com/stdlib-js/stdlib/issues/3237), [#3238](https://github.com/stdlib-js/stdlib/issues/3238), [#3378](https://github.com/stdlib-js/stdlib/issues/3378), [#3384](https://github.com/stdlib-js/stdlib/issues/3384), [#3385](https://github.com/stdlib-js/stdlib/issues/3385), [#3401](https://github.com/stdlib-js/stdlib/issues/3401), [#3414](https://github.com/stdlib-js/stdlib/issues/3414), [#3445](https://github.com/stdlib-js/stdlib/issues/3445), [#3446](https://github.com/stdlib-js/stdlib/issues/3446), [#3447](https://github.com/stdlib-js/stdlib/issues/3447), [#3671](https://github.com/stdlib-js/stdlib/issues/3671)
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</section>
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<details>
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- [`c77a433`](https://github.com/stdlib-js/stdlib/commit/c77a433d6e33ad5f4879d32211d8cfdb4e5fa2c6) - **feat:** add C implementation for `stats/base/dists/betaprime/variance` [(#3460)](https://github.com/stdlib-js/stdlib/pull/3460) _(by Aayush Khanna, Philipp Burckhardt, stdlib-bot)_
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- [`0fc07d1`](https://github.com/stdlib-js/stdlib/commit/0fc07d1722a3da70464b37d4de5f6a762468f85e) - **feat:** add C implementation for `stats/base/dists/betaprime/skewness` [(#3462)](https://github.com/stdlib-js/stdlib/pull/3462) _(by Aayush Khanna, Philipp Burckhardt, stdlib-bot)_
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- [`31faa3e`](https://github.com/stdlib-js/stdlib/commit/31faa3e761d92fe94a35d941bed6640380e21b37) - **feat:** add C implementation for `stats/base/dists/arcsine/kurtosis` [(#3388)](https://github.com/stdlib-js/stdlib/pull/3388) _(by Aayush Khanna, Philipp Burckhardt, stdlib-bot)_
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- [`e9d539e`](https://github.com/stdlib-js/stdlib/commit/e9d539ed6f0185d2455a45b5e29bd50d5c556db5) - **feat:** add C implementation for `stats/base/dists/invgamma/entropy` [(#3682)](https://github.com/stdlib-js/stdlib/pull/3682) _(by Aayush Khanna, Philipp Burckhardt, stdlib-bot)_

base/dists/betaprime/variance/README.md

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<!-- /.examples -->
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<!-- C interface documentation. -->
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* * *
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<section class="c">
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## C APIs
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<!-- Section to include introductory text. Make sure to keep an empty line after the intro `section` element and another before the `/section` close. -->
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<section class="intro">
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</section>
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<!-- /.intro -->
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<!-- C usage documentation. -->
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<section class="usage">
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### Usage
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```c
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#include "stdlib/stats/base/dists/betaprime/variance.h"
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```
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#### stdlib_base_dists_betaprime_variance( alpha, beta )
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Returns the variance of a beta prime distribution.
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```c
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double out = stdlib_base_dists_betaprime_variance( 1.0, 3.0 );
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// returns ~0.75
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```
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The function accepts the following arguments:
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- **alpha**: `[in] double` first shape parameter.
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- **beta**: `[in] double` second shape parameter.
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```c
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double stdlib_base_dists_betaprime_variance( const double alpha, const double beta );
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```
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</section>
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<!-- /.usage -->
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<!-- C API usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
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<section class="notes">
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</section>
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<!-- /.notes -->
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<!-- C API usage examples. -->
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<section class="examples">
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### Examples
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```c
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#include "stdlib/stats/base/dists/betaprime/variance.h"
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#include <stdlib.h>
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#include <stdio.h>
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static double random_uniform( const double min, const double max ) {
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double v = (double)rand() / ( (double)RAND_MAX + 1.0 );
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return min + ( v * ( max - min ) );
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}
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int main( void ) {
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double alpha;
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double beta;
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double y;
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int i;
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for ( i = 0; i < 25; i++ ) {
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alpha = random_uniform( 0, 20 );
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beta = random_uniform( 0, 20 ) + 2.0;
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y = stdlib_base_dists_betaprime_variance( alpha, beta );
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printf( "α: %lf, β: %lf, Var(X;α,β): %lf", alpha, beta, y );
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}
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}
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```
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</section>
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<!-- /.examples -->
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</section>
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<!-- /.c -->
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<!-- Section to include cited references. If references are included, add a horizontal rule *before* the section. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
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<section class="references">

base/dists/betaprime/variance/benchmark/benchmark.js

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// MODULES //
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var bench = require( '@stdlib/bench' );
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var Float64Array = require( '@stdlib/array/float64' );
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var randu = require( '@stdlib/random/base/randu' );
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var isnan = require( '@stdlib/math/base/assert/is-nan' );
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var EPS = require( '@stdlib/constants/float64/eps' );
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bench( pkg, function benchmark( b ) {
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var alpha;
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var beta;
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var len;
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var y;
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var i;
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len = 100;
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alpha = new Float64Array( len );
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beta = new Float64Array( len );
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for ( i = 0; i < len; i++ ) {
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alpha[ i ] = ( randu() * 20.0 ) + EPS;
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beta[ i ] = ( randu() * 20.0 ) + 2.0 + EPS;
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}
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b.tic();
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alpha = ( randu()*10.0 ) + EPS;
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beta = ( randu()*10.0 ) + 2.0 + EPS;
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y = variance( alpha, beta );
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y = variance( alpha[ i % len ], beta[ i % len ] );
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if ( isnan( y ) ) {
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b.fail( 'should not return NaN' );
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}
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/**
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* @license Apache-2.0
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*
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* Copyright (c) 2024 The Stdlib Authors.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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'use strict';
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// MODULES //
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var resolve = require( 'path' ).resolve;
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var bench = require( '@stdlib/bench' );
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var Float64Array = require( '@stdlib/array/float64' );
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var tryRequire = require( '@stdlib/utils/try-require' );
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var randu = require( '@stdlib/random/base/randu' );
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var isnan = require( '@stdlib/math/base/assert/is-nan' );
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var EPS = require( '@stdlib/constants/float64/eps' );
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var pkg = require( './../package.json' ).name;
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// VARIABLES //
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var variance = tryRequire( resolve( __dirname, './../lib/native.js' ) );
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var opts = {
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'skip': ( variance instanceof Error )
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};
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// MAIN //
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bench( pkg+'::native', opts, function benchmark( b ) {
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var alpha;
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var beta;
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var len;
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var y;
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var i;
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len = 100;
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alpha = new Float64Array( len );
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beta = new Float64Array( len );
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for ( i = 0; i < len; i++ ) {
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alpha[ i ] = ( randu() * 20.0 ) + EPS;
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beta[ i ] = ( randu() * 20.0 ) + 2.0 + EPS;
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}
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b.tic();
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for ( i = 0; i < b.iterations; i++ ) {
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y = variance( alpha[ i % len ], beta[ i % len ] );
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if ( isnan( y ) ) {
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b.fail( 'should not return NaN' );
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}
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}
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b.toc();
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if ( isnan( y ) ) {
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b.fail( 'should not return NaN' );
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}
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b.pass( 'benchmark finished' );
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b.end();
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});

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