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CHANGELOG.md

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<section class="release" id="unreleased">
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## Unreleased (2025-03-29)
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## Unreleased (2025-04-02)
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<section class="features">
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### Features
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- [`41d0632`](https://github.com/stdlib-js/stdlib/commit/41d0632145a36b71711b27c0ee7add3c0434c7f5) - refactor and add protocol support to `stats/base/nanvariancewd` [(#6023)](https://github.com/stdlib-js/stdlib/pull/6023)
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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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[#5677](https://github.com/stdlib-js/stdlib/issues/5677)
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</section>
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<!-- /.issues -->
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<section class="commits">
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### Commits
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<details>
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- [`41d0632`](https://github.com/stdlib-js/stdlib/commit/41d0632145a36b71711b27c0ee7add3c0434c7f5) - **feat:** refactor and add protocol support to `stats/base/nanvariancewd` [(#6023)](https://github.com/stdlib-js/stdlib/pull/6023) _(by Prajjwal Bajpai, Athan Reines, Aayush Khanna)_
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- [`4de7fc4`](https://github.com/stdlib-js/stdlib/commit/4de7fc4b59fa279a67b642213e90760eaf5f7b88) - **refactor:** update paths _(by Aayush Khanna)_
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</details>
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### Contributors
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A total of 1 person contributed to this release. Thank you to this contributor:
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A total of 3 people contributed to this release. Thank you to the following contributors:
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- Aayush Khanna
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- Athan Reines
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- Prajjwal Bajpai
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</section>
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CONTRIBUTORS

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Rylan Yang <[email protected]>
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SAHIL KUMAR <[email protected]>
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SHIVAM YADAV <[email protected]>
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Sahil Goyal <[email protected]>
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Sai Avinash <[email protected]>
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Sai Srikar Dumpeti <[email protected]>
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Sanchay Ketan Sinha <[email protected]>
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Sarthak Paandey <[email protected]>
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ekambains <[email protected]>
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fadiothman22 <[email protected]>
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lohithganni <[email protected]>
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olenkabilonizhka <[email protected]>
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pranav-1720 <[email protected]>
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rahulrangers <[email protected]>

README.md

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var nanvariancewd = require( '@stdlib/stats-base-nanvariancewd' );
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```
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#### nanvariancewd( N, correction, x, stride )
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#### nanvariancewd( N, correction, x, strideX )
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Computes the [variance][variance] of a strided array `x` ignoring `NaN` values and using Welford's algorithm.
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Computes the [variance][variance] of a strided array ignoring `NaN` values and using Welford's algorithm.
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```javascript
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var x = [ 1.0, -2.0, NaN, 2.0 ];
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- **N**: number of indexed elements.
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- **correction**: degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [variance][variance] according to `n-c` where `c` corresponds to the provided degrees of freedom adjustment and `n` corresponds to the number of non-`NaN` indexed elements. When computing the [variance][variance] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the unbiased sample [variance][variance], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction).
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- **x**: input [`Array`][mdn-array] or [`typed array`][mdn-typed-array].
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- **stride**: index increment for `x`.
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- **strideX**: stride length for `x`.
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The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the [variance][variance] of every other element in `x`,
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The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the [variance][variance] of every other element in `x`,
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```javascript
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var floor = require( '@stdlib/math-base-special-floor' );
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var x = [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0, NaN ];
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var N = floor( x.length / 2 );
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var v = nanvariancewd( N, 1, x, 2 );
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var v = nanvariancewd( 5, 1, x, 2 );
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// returns 6.25
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```
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Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views.
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<!-- eslint-disable stdlib/capitalized-comments -->
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<!-- eslint-disable stdlib/capitalized-comments, max-len -->
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```javascript
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var Float64Array = require( '@stdlib/array-float64' );
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var floor = require( '@stdlib/math-base-special-floor' );
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var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN ] );
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var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ] );
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var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
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var N = floor( x0.length / 2 );
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var v = nanvariancewd( N, 1, x1, 2 );
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var v = nanvariancewd( 5, 1, x1, 2 );
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// returns 6.25
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```
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#### nanvariancewd.ndarray( N, correction, x, stride, offset )
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#### nanvariancewd.ndarray( N, correction, x, strideX, offsetX )
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Computes the [variance][variance] of a strided array ignoring `NaN` values and using Welford's algorithm and alternative indexing semantics.
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The function has the following additional parameters:
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- **offset**: starting index for `x`.
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- **offsetX**: starting index for `x`.
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While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the [variance][variance] for every other value in `x` starting from the second value
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While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the [variance][variance] for every other element in the strided array starting from the second element
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var floor = require( '@stdlib/math-base-special-floor' );
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var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ];
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var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ];
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var N = floor( x.length / 2 );
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var v = nanvariancewd.ndarray( N, 1, x, 2, 1 );
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var v = nanvariancewd.ndarray( 5, 1, x, 2, 1 );
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```
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## Notes
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- If `N <= 0`, both functions return `NaN`.
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- Both functions support array-like objects having getter and setter accessors for array element access (e.g., [`@stdlib/array-base/accessor`][@stdlib/array/base/accessor]).
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- If `n - c` is less than or equal to `0` (where `c` corresponds to the provided degrees of freedom adjustment and `n` corresponds to the number of non-`NaN` indexed elements), both functions return `NaN`.
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- Depending on the environment, the typed versions ([`dnanvariancewd`][@stdlib/stats/strided/dnanvariancewd], [`snanvariancewd`][@stdlib/stats/base/snanvariancewd], etc.) are likely to be significantly more performant.
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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 uniform = require( '@stdlib/random-base-uniform' );
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var filledarrayBy = require( '@stdlib/array-filled-by' );
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var nanvariancewd = require( '@stdlib/stats-base-nanvariancewd' );
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var bernoulli = require( '@stdlib/random-base-bernoulli' );
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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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function rand() {
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if ( bernoulli( 0.8 ) < 1 ) {
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return NaN;
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}
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return uniform( -50.0, 50.0 );
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}
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var x = filledarrayBy( 10, 'float64', rand );
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console.log( x );
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var v = nanvariancewd( x.length, 1, x, 1 );
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[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray
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[@stdlib/array/base/accessor]: https://github.com/stdlib-js/array-base-accessor
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[@welford:1962a]: https://doi.org/10.1080/00401706.1962.10490022
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[@vanreeken:1968a]: https://doi.org/10.1145/362929.362961

benchmark/benchmark.js

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// MODULES //
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var bench = require( '@stdlib/bench-harness' );
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var randu = require( '@stdlib/random-base-randu' );
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var uniform = require( '@stdlib/random-base-uniform' );
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var bernoulli = require( '@stdlib/random-base-bernoulli' );
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var filledarrayBy = require( '@stdlib/array-filled-by' );
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var isnan = require( '@stdlib/math-base-assert-is-nan' );
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var nanvariancewd = require( './../lib/main.js' );
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// FUNCTIONS //
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/**
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* Returns a random value or `NaN`.
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*
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* @private
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*/
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benchmark/benchmark.ndarray.js

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dist/index.js

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