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feat: add accessor protocol support to
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‎CONTRIBUTORS

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@@ -17,6 +17,7 @@ Ali Salesi <[email protected]>
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Aman Bhansali <[email protected]>
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Amit Jimiwal <[email protected]>
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Anudeep Sanapala <[email protected]>
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Aryan Bhirud <[email protected]>
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Athan Reines <[email protected]>
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Ayaka <[email protected]>
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Brendan Graetz <[email protected]>

‎lib/node_modules/@stdlib/stats/base/variancepn/README.md

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@license Apache-2.0
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Copyright (c) 2020 The Stdlib Authors.
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Copyright (c) 2025 The Stdlib Authors.
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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.
@@ -197,18 +197,12 @@ var v = variancepn.ndarray( N, 1, x, 2, 1 );
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<!-- eslint no-undef: "error" -->
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```javascript
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var randu = require( '@stdlib/random/base/randu' );
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var round = require( '@stdlib/math/base/special/round' );
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var Float64Array = require( '@stdlib/array/float64' );
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var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
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var variancepn = require( '@stdlib/stats/base/variancepn' );
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var x;
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var i;
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x = new Float64Array( 10 );
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for ( i = 0; i < x.length; i++ ) {
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x[ i ] = round( (randu()*100.0) - 50.0 );
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}
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var x = discreteUniform( 10, -50, 50, {
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'dtype': 'float64'
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});
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console.log( x );
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var v = variancepn( x.length, 1, x, 1 );

‎lib/node_modules/@stdlib/stats/base/variancepn/benchmark/benchmark.js

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/**
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* @license Apache-2.0
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*
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* Copyright (c) 2020 The Stdlib Authors.
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* Copyright (c) 2025 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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// MODULES //
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var bench = require( '@stdlib/bench' );
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var randu = require( '@stdlib/random/base/randu' );
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var uniform = require( '@stdlib/random/array/uniform' );
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var isnan = require( '@stdlib/math/base/assert/is-nan' );
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var pow = require( '@stdlib/math/base/special/pow' );
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var pkg = require( './../package.json' ).name;
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var variancepn = require( './../lib/variancepn.js' );
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// VARIABLES //
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var options = {
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'dtype': 'generic'
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};
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// FUNCTIONS //
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/**
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* @returns {Function} benchmark function
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*/
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function createBenchmark( len ) {
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var x;
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var i;
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x = [];
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for ( i = 0; i < len; i++ ) {
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x.push( ( randu()*20.0 ) - 10.0 );
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}
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var x = uniform( len, -10, 10, options );
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return benchmark;
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function benchmark( b ) {

‎lib/node_modules/@stdlib/stats/base/variancepn/benchmark/benchmark.ndarray.js

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/**
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* @license Apache-2.0
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*
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* Copyright (c) 2020 The Stdlib Authors.
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* Copyright (c) 2025 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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// MODULES //
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var bench = require( '@stdlib/bench' );
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var randu = require( '@stdlib/random/base/randu' );
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var uniform = require( '@stdlib/random/array/uniform' );
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var isnan = require( '@stdlib/math/base/assert/is-nan' );
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var pow = require( '@stdlib/math/base/special/pow' );
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var pkg = require( './../package.json' ).name;
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var variancepn = require( './../lib/ndarray.js' );
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// VARIABLES //
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var options = {
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'dtype': 'generic'
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};
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// FUNCTIONS //
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/**
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* @returns {Function} benchmark function
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*/
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function createBenchmark( len ) {
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var x;
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var i;
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x = [];
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for ( i = 0; i < len; i++ ) {
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x.push( ( randu()*20.0 ) - 10.0 );
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}
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var x = uniform( len, -10, 10, options );
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return benchmark;
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function benchmark( b ) {

‎lib/node_modules/@stdlib/stats/base/variancepn/docs/repl.txt

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{{alias}}( N, correction, x, stride )
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Computes the variance of a strided array using a two-pass algorithm.
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The `N` and `stride` parameters determine which elements in `x` are accessed
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at runtime.
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The `N` and stride parameters determine which elements in the strided array
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are accessed at runtime.
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Indexing is relative to the first index. To introduce an offset, use a typed
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array view.
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Input array.
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stride: integer
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Index increment.
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Stride length.
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Returns
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-------
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> {{alias}}( x.length, 1, x, 1 )
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~4.3333
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// Using `N` and `stride` parameters:
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// Using `N` and stride parameters:
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> x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];
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> var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
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> var stride = 2;
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> {{alias}}( N, 1, x, stride )
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> {{alias}}( 3, 1, x, stride )
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~4.3333
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// Using view offsets:
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> var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );
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> var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );
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> N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );
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> stride = 2;
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> {{alias}}( N, 1, x1, stride )
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> {{alias}}( 3, 1, x1, stride )
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~4.3333
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{{alias}}.ndarray( N, correction, x, stride, offset )
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Computes the variance of a strided array using a two-pass algorithm and
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alternative indexing semantics.
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Input array.
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stride: integer
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Index increment.
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Stride length.
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offset: integer
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Starting index.
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// Using offset parameter:
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> var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];
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> var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
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> {{alias}}.ndarray( N, 1, x, 2, 1 )
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> {{alias}}.ndarray( 3, 1, x, 2, 1 )
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~4.3333
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See Also

‎lib/node_modules/@stdlib/stats/base/variancepn/docs/types/index.d.ts

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/*
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* @license Apache-2.0
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*
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* Copyright (c) 2020 The Stdlib Authors.
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* Copyright (c) 2025 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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/// <reference types="@stdlib/types"/>
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import { NumericArray } from '@stdlib/types/array';
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import { NumericArray, Collection, AccessorArrayLike } from '@stdlib/types/array';
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/**
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* Input array.
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*/
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type InputArray = NumericArray | Collection<number> | AccessorArrayLike<number>;
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/**
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* Interface describing `variancepn`.
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*/
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interface Routine {
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/**
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* Computes the variance of a strided array using a two-pass algorithm.
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* Computes the variance of a strided array using a two-pass algorithm and alternative indexing semantics.
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*
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* @param N - number of indexed elements
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* @param correction - degrees of freedom adjustment
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* @example
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* var x = [ 1.0, -2.0, 2.0 ];
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*
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* var v = variancepn( x.length, 1, x, 1 );
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* var v = variancepn( x.length, 1, x, 1, 0 );
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* // returns ~4.3333
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*/
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( N: number, correction: number, x: NumericArray, stride: number ): number;
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( N: number, correction: number, x: NumericArray | InputArray, stride: number ): number;
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/**
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* Computes the variance of a strided array using a two-pass algorithm and alternative indexing semantics.
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* var v = variancepn.ndarray( x.length, 1, x, 1, 0 );
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* // returns ~4.3333
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*/
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ndarray( N: number, correction: number, x: NumericArray, stride: number, offset: number ): number;
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ndarray( N: number, correction: number, x: InputArray, stride: number, offset: number ): number;
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}
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/**

‎lib/node_modules/@stdlib/stats/base/variancepn/docs/types/test.ts

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/*
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* @license Apache-2.0
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*
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* Copyright (c) 2020 The Stdlib Authors.
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* Copyright (c) 2025 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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* limitations under the License.
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*/
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import AccessorArray = require( '@stdlib/array/base/accessor' );
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import variancepn = require( './index' );
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const x = new Float64Array( 10 );
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variancepn( x.length, 1, x, 1 ); // $ExpectType number
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variancepn( x.length, 1, new AccessorArray( x ), 1 ); // $ExpectType number
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}
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// The compiler throws an error if the function is provided a first argument which is not a number...
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const x = new Float64Array( 10 );
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variancepn.ndarray( x.length, 1, x, 1, 0 ); // $ExpectType number
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variancepn.ndarray( x.length, 1, new AccessorArray( x ), 1, 0 ); // $ExpectType number
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}
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// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number...

‎lib/node_modules/@stdlib/stats/base/variancepn/examples/index.js

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/**
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* @license Apache-2.0
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*
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* Copyright (c) 2020 The Stdlib Authors.
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* Copyright (c) 2025 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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'use strict';
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var randu = require( '@stdlib/random/base/randu' );
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var round = require( '@stdlib/math/base/special/round' );
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var Float64Array = require( '@stdlib/array/float64' );
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var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
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var variancepn = require( './../lib' );
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var x;
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var i;
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x = new Float64Array( 10 );
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for ( i = 0; i < x.length; i++ ) {
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x[ i ] = round( (randu()*100.0) - 50.0 );
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}
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var x = discreteUniform( 10, -50, 50, {
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'dtype': 'float64'
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});
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console.log( x );
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var v = variancepn( x.length, 1, x, 1 );

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