diff --git a/lib/node_modules/@stdlib/stats/base/variancepn/README.md b/lib/node_modules/@stdlib/stats/base/variancepn/README.md
index 5775585ee772..d5cdc5b2e515 100644
--- a/lib/node_modules/@stdlib/stats/base/variancepn/README.md
+++ b/lib/node_modules/@stdlib/stats/base/variancepn/README.md
@@ -2,7 +2,7 @@
@license Apache-2.0
-Copyright (c) 2020 The Stdlib Authors.
+Copyright (c) 2025 The Stdlib Authors.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
@@ -88,8 +88,10 @@ The use of the term `n-1` is commonly referred to as Bessel's correction. Note,
+
+
## Usage
@@ -98,7 +100,7 @@ The use of the term `n-1` is commonly referred to as Bessel's correction. Note,
var variancepn = require( '@stdlib/stats/base/variancepn' );
```
-#### variancepn( N, correction, x, stride )
+#### variancepn( N, correction, x, strideX )
Computes the [variance][variance] of a strided array `x` using a two-pass algorithm.
@@ -115,17 +117,14 @@ The function has the following parameters:
- **N**: number of indexed elements.
- **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. 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).
- **x**: input [`Array`][mdn-array] or [`typed array`][mdn-typed-array].
-- **stride**: index increment for `x`.
+- **strideX**: stride length for `x`.
-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`,
+The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the [variance][variance] of every other element in `x`,
```javascript
-var floor = require( '@stdlib/math/base/special/floor' );
-
var x = [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ];
-var N = floor( x.length / 2 );
-var v = variancepn( N, 1, x, 2 );
+var v = variancepn( 4, 1, x, 2 );
// returns 6.25
```
@@ -135,18 +134,15 @@ Note that indexing is relative to the first index. To introduce an offset, use [
```javascript
var Float64Array = require( '@stdlib/array/float64' );
-var floor = require( '@stdlib/math/base/special/floor' );
var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
-var N = floor( x0.length / 2 );
-
-var v = variancepn( N, 1, x1, 2 );
+var v = variancepn( 4, 1, x1, 2 );
// returns 6.25
```
-#### variancepn.ndarray( N, correction, x, stride, offset )
+#### variancepn.ndarray( N, correction, x, strideX, offsetX )
Computes the [variance][variance] of a strided array using a two-pass algorithm and alternative indexing semantics.
@@ -160,24 +156,23 @@ var v = variancepn.ndarray( N, 1, x, 1, 0 );
The function has the following additional parameters:
-- **offset**: starting index for `x`.
+- **offsetX**: starting index for `x`.
-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
+While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer , the offset parameters support indexing semantics based on starting indices. For example, to calculate the [variance][variance] for every other value in `x` starting from the second value
```javascript
-var floor = require( '@stdlib/math/base/special/floor' );
-
var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ];
-var N = floor( x.length / 2 );
-var v = variancepn.ndarray( N, 1, x, 2, 1 );
+var v = variancepn.ndarray( 4, 1, x, 2, 1 );
// returns 6.25
```
+
+
## Notes
@@ -185,11 +180,14 @@ var v = variancepn.ndarray( N, 1, x, 2, 1 );
- If `N <= 0`, both functions return `NaN`.
- If `N - c` is less than or equal to `0` (where `c` corresponds to the provided degrees of freedom adjustment), both functions return `NaN`.
- Depending on the environment, the typed versions ([`dvariancepn`][@stdlib/stats/base/dvariancepn], [`svariancepn`][@stdlib/stats/base/svariancepn], etc.) are likely to be significantly more performant.
+- 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]).
+
+
## Examples
@@ -197,18 +195,13 @@ var v = variancepn.ndarray( N, 1, x, 2, 1 );
```javascript
-var randu = require( '@stdlib/random/base/randu' );
-var round = require( '@stdlib/math/base/special/round' );
+var uniform = require( '@stdlib/random/array/uniform' );
var Float64Array = require( '@stdlib/array/float64' );
var variancepn = require( '@stdlib/stats/base/variancepn' );
-var x;
-var i;
-
-x = new Float64Array( 10 );
-for ( i = 0; i < x.length; i++ ) {
- x[ i ] = round( (randu()*100.0) - 50.0 );
-}
+var x = uniform( 10, -50.0, 50.0, {
+ 'dtype': 'float64'
+});
console.log( x );
var v = variancepn( x.length, 1, x, 1 );
@@ -217,6 +210,7 @@ console.log( v );
+
* * *
@@ -230,6 +224,7 @@ console.log( v );
+
@@ -247,16 +242,21 @@ console.log( v );
+
+
+
[variance]: https://en.wikipedia.org/wiki/Variance
[mdn-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Array
+[@stdlib/array/base/accessor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/accessor
+
[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray
[@stdlib/stats/base/svariancepn]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/svariancepn
@@ -277,6 +277,8 @@ console.log( v );
+
+
diff --git a/lib/node_modules/@stdlib/stats/base/variancepn/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/variancepn/benchmark/benchmark.js
index 24b5d4603b04..9e8968de7cbf 100644
--- a/lib/node_modules/@stdlib/stats/base/variancepn/benchmark/benchmark.js
+++ b/lib/node_modules/@stdlib/stats/base/variancepn/benchmark/benchmark.js
@@ -1,7 +1,7 @@
/**
* @license Apache-2.0
*
-* Copyright (c) 2020 The Stdlib Authors.
+* Copyright (c) 2025 The Stdlib Authors.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
@@ -21,13 +21,20 @@
// MODULES //
var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
var isnan = require( '@stdlib/math/base/assert/is-nan' );
var pow = require( '@stdlib/math/base/special/pow' );
+var uniform = require( '@stdlib/random/array/uniform' );
var pkg = require( './../package.json' ).name;
var variancepn = require( './../lib/variancepn.js' );
+// VARIABLES //
+
+var options = {
+ 'dtype': 'generic'
+};
+
+
// FUNCTIONS //
/**
@@ -38,13 +45,7 @@ var variancepn = require( './../lib/variancepn.js' );
* @returns {Function} benchmark function
*/
function createBenchmark( len ) {
- var x;
- var i;
-
- x = [];
- for ( i = 0; i < len; i++ ) {
- x.push( ( randu()*20.0 ) - 10.0 );
- }
+ var x = uniform( len, -10.0, 10.0, options );
return benchmark;
function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/variancepn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/variancepn/benchmark/benchmark.ndarray.js
index a60d78aca901..682f726db404 100644
--- a/lib/node_modules/@stdlib/stats/base/variancepn/benchmark/benchmark.ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/variancepn/benchmark/benchmark.ndarray.js
@@ -1,7 +1,7 @@
/**
* @license Apache-2.0
*
-* Copyright (c) 2020 The Stdlib Authors.
+* Copyright (c) 2025 The Stdlib Authors.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
@@ -21,13 +21,20 @@
// MODULES //
var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var uniform = require( '@stdlib/random/array/uniform' );
var pow = require( '@stdlib/math/base/special/pow' );
var pkg = require( './../package.json' ).name;
var variancepn = require( './../lib/ndarray.js' );
+// VARIABLES //
+
+var options = {
+ 'dtype': 'generic'
+};
+
+
// FUNCTIONS //
/**
@@ -38,13 +45,7 @@ var variancepn = require( './../lib/ndarray.js' );
* @returns {Function} benchmark function
*/
function createBenchmark( len ) {
- var x;
- var i;
-
- x = [];
- for ( i = 0; i < len; i++ ) {
- x.push( ( randu()*20.0 ) - 10.0 );
- }
+ var x = uniform( len, -10.0, 10.0, options );
return benchmark;
function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/variancepn/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/variancepn/docs/repl.txt
index e3bffde92299..0f56f035aa3d 100644
--- a/lib/node_modules/@stdlib/stats/base/variancepn/docs/repl.txt
+++ b/lib/node_modules/@stdlib/stats/base/variancepn/docs/repl.txt
@@ -1,12 +1,12 @@
-{{alias}}( N, correction, x, stride )
- Computes the variance of a strided array using a two-pass algorithm.
+{{alias}}( N, correction, x, strideX )
+ Computes the variance of a strided array (two-pass algorithm).
- The `N` and `stride` parameters determine which elements in `x` are accessed
- at runtime.
+ The `N` and stride parameters determine which elements in the
+ strided arrays are accessed at runtime.
- Indexing is relative to the first index. To introduce an offset, use a typed
- array view.
+ Indexing is relative to the first index. To introduce
+ an offset, use a typed array view.
If `N <= 0`, the function returns `NaN`.
@@ -30,8 +30,8 @@
x: Array|TypedArray
Input array.
- stride: integer
- Index increment.
+ strideX: integer
+ Stride length.
Returns
-------
@@ -43,24 +43,23 @@
// Standard Usage:
> var x = [ 1.0, -2.0, 2.0 ];
> {{alias}}( x.length, 1, x, 1 )
- ~4.3333
+ 4.333333333333334
- // Using `N` and `stride` parameters:
+ // Using `N` and `strideX` parameters:
> x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];
- > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
- > var stride = 2;
- > {{alias}}( N, 1, x, stride )
- ~4.3333
+ > var strideX = 2;
+ > {{alias}}( 4, 1, x, strideX )
+ NaN
// Using view offsets:
> var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );
> var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );
- > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );
- > stride = 2;
- > {{alias}}( N, 1, x1, stride )
- ~4.3333
+ > strideX = 2;
+ > {{alias}}( 4, 1, x1, strideX )
+ NaN
+
-{{alias}}.ndarray( N, correction, x, stride, offset )
+{{alias}}.ndarray( N, correction, x, strideX, offset )
Computes the variance of a strided array using a two-pass algorithm and
alternative indexing semantics.
@@ -88,8 +87,8 @@
x: Array|TypedArray
Input array.
- stride: integer
- Index increment.
+ strideX: integer
+ Stride length.
offset: integer
Starting index.
@@ -108,10 +107,9 @@
// Using offset parameter:
> var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];
- > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
- > {{alias}}.ndarray( N, 1, x, 2, 1 )
- ~4.3333
+ > {{alias}}.ndarray( 4, 1, x, 2, 1 )
+ NaN
+
See Also
--------
-
diff --git a/lib/node_modules/@stdlib/stats/base/variancepn/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/variancepn/docs/types/index.d.ts
index 7db62141e6a1..48eed198e106 100644
--- a/lib/node_modules/@stdlib/stats/base/variancepn/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/variancepn/docs/types/index.d.ts
@@ -1,7 +1,7 @@
/*
* @license Apache-2.0
*
-* Copyright (c) 2020 The Stdlib Authors.
+* Copyright (c) 2025 The Stdlib Authors.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
@@ -20,7 +20,12 @@
///
-import { NumericArray } from '@stdlib/types/array';
+import { NumericArray, Collection, AccessorArrayLike } from '@stdlib/types/array';
+
+/**
+* Input array.
+*/
+type InputArray = NumericArray | Collection | AccessorArrayLike;
/**
* Interface describing `variancepn`.
@@ -32,7 +37,7 @@ interface Routine {
* @param N - number of indexed elements
* @param correction - degrees of freedom adjustment
* @param x - input array
- * @param stride - stride length
+ * @param strideX - stride length
* @returns variance
*
* @example
@@ -41,7 +46,7 @@ interface Routine {
* var v = variancepn( x.length, 1, x, 1 );
* // returns ~4.3333
*/
- ( N: number, correction: number, x: NumericArray, stride: number ): number;
+ ( N: number, correction: number, x: InputArray, strideX: number ): number;
/**
* Computes the variance of a strided array using a two-pass algorithm and alternative indexing semantics.
@@ -49,8 +54,8 @@ interface Routine {
* @param N - number of indexed elements
* @param correction - degrees of freedom adjustment
* @param x - input array
- * @param stride - stride length
- * @param offset - starting index
+ * @param strideX - stride length
+ * @param offsetX - starting index
* @returns variance
*
* @example
@@ -59,7 +64,7 @@ interface Routine {
* var v = variancepn.ndarray( x.length, 1, x, 1, 0 );
* // returns ~4.3333
*/
- ndarray( N: number, correction: number, x: NumericArray, stride: number, offset: number ): number;
+ ndarray( N: number, correction: number, x: InputArray, strideX: number, offsetX: number ): number;
}
/**
@@ -68,7 +73,7 @@ interface Routine {
* @param N - number of indexed elements
* @param correction - degrees of freedom adjustment
* @param x - input array
-* @param stride - stride length
+* @param strideX - stride length
* @returns variance
*
* @example
diff --git a/lib/node_modules/@stdlib/stats/base/variancepn/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/variancepn/docs/types/test.ts
index 146d3b4a5983..6d421920bf71 100644
--- a/lib/node_modules/@stdlib/stats/base/variancepn/docs/types/test.ts
+++ b/lib/node_modules/@stdlib/stats/base/variancepn/docs/types/test.ts
@@ -16,6 +16,7 @@
* limitations under the License.
*/
+import AccessorArray = require( '@stdlib/array/base/accessor' );
import variancepn = require( './index' );
@@ -26,6 +27,7 @@ import variancepn = require( './index' );
const x = new Float64Array( 10 );
variancepn( x.length, 1, x, 1 ); // $ExpectType number
+ variancepn( x.length, 1, new AccessorArray( x ), 1 ); // $ExpectType number
}
// The compiler throws an error if the function is provided a first argument which is not a number...
@@ -101,6 +103,7 @@ import variancepn = require( './index' );
const x = new Float64Array( 10 );
variancepn.ndarray( x.length, 1, x, 1, 0 ); // $ExpectType number
+ variancepn.ndarray( x.length, 1, new AccessorArray( x ), 1, 0 ); // $ExpectType number
}
// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number...
diff --git a/lib/node_modules/@stdlib/stats/base/variancepn/examples/index.js b/lib/node_modules/@stdlib/stats/base/variancepn/examples/index.js
index c128c57945e2..035da9739b20 100644
--- a/lib/node_modules/@stdlib/stats/base/variancepn/examples/index.js
+++ b/lib/node_modules/@stdlib/stats/base/variancepn/examples/index.js
@@ -1,7 +1,7 @@
/**
* @license Apache-2.0
*
-* Copyright (c) 2020 The Stdlib Authors.
+* Copyright (c) 2025 The Stdlib Authors.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
@@ -18,18 +18,14 @@
'use strict';
-var randu = require( '@stdlib/random/base/randu' );
-var round = require( '@stdlib/math/base/special/round' );
-var Float64Array = require( '@stdlib/array/float64' );
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
var variancepn = require( './../lib' );
var x;
-var i;
-x = new Float64Array( 10 );
-for ( i = 0; i < x.length; i++ ) {
- x[ i ] = round( (randu()*100.0) - 50.0 );
-}
+x = discreteUniform( 10, -50, 50, {
+ 'dtype': 'float64'
+});
console.log( x );
var v = variancepn( x.length, 1, x, 1 );
diff --git a/lib/node_modules/@stdlib/stats/base/variancepn/lib/accessors.js b/lib/node_modules/@stdlib/stats/base/variancepn/lib/accessors.js
new file mode 100644
index 000000000000..702a046db8f0
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/variancepn/lib/accessors.js
@@ -0,0 +1,102 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var gsumpw = require( '@stdlib/blas/ext/base/gsumpw' ).ndarray;
+
+
+// MAIN //
+
+/**
+* Computes the variance of a strided array using a two-pass algorithm.
+*
+* ## Method
+*
+* - This implementation uses a two-pass approach, as suggested by Neely (1966).
+*
+* ## References
+*
+* - Neely, Peter M. 1966. "Comparison of Several Algorithms for Computation of Means, Standard Deviations and Correlation Coefficients." _Communications of the ACM_ 9 (7). Association for Computing Machinery: 496–99. doi:[10.1145/365719.365958](https://doi.org/10.1145/365719.365958).
+* - Schubert, Erich, and Michael Gertz. 2018. "Numerically Stable Parallel Computation of (Co-)Variance." In _Proceedings of the 30th International Conference on Scientific and Statistical Database Management_. New York, NY, USA: Association for Computing Machinery. doi:[10.1145/3221269.3223036](https://doi.org/10.1145/3221269.3223036).
+*
+* @param {PositiveInteger} N - number of indexed elements
+* @param {number} correction - degrees of freedom adjustment
+* @param {Object} x - input array object
+* @param {Collection} x.data - input array data
+* @param {Array} x.accessors - array element accessors
+* @param {integer} strideX - stride length for 'x'
+* @param {NonNegativeInteger} offsetX - starting index for 'x'
+* @returns {Object} variance
+*
+* @example
+* var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' );
+* var arraylike2object = require( '@stdlib/array/base/arraylike2object' );
+*
+* var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ];
+*
+* var v = variancepn( 4, 1, arraylike2object( toAccessorArray( x ) ), 2, 1 );
+* // returns 6.25
+*/
+function variancepn( N, correction, x, strideX, offsetX ) {
+ var xbuf;
+ var get;
+ var mu;
+ var ix;
+ var M2;
+ var M;
+ var d;
+ var n;
+ var i;
+
+ // Cache references to array data:
+ xbuf = x.data;
+
+ // Cache references to element accessors:
+ get = x.accessors[ 0 ];
+
+ n = N - correction;
+ if ( N <= 0 || n <= 0.0 ) {
+ return NaN;
+ }
+ if ( N === 1 || strideX === 0 ) {
+ return 0.0;
+ }
+ // Compute an estimate for the mean:
+ /* eslint-disable-next-line no-underscore-dangle */
+ mu = gsumpw( N, xbuf._buffer, strideX, offsetX ) / N;
+
+ // Compute the variance...
+ ix = offsetX;
+ M2 = 0.0;
+ M = 0.0;
+ for ( i = 0; i < N; i++ ) {
+ d = get( xbuf, ix ) - mu;
+ M2 += d * d;
+ M += d;
+ ix += strideX;
+ }
+ return (M2/n) - ((M/N)*(M/n));
+}
+
+
+// EXPORTS //
+
+module.exports = variancepn;
diff --git a/lib/node_modules/@stdlib/stats/base/variancepn/lib/index.js b/lib/node_modules/@stdlib/stats/base/variancepn/lib/index.js
index 9c1e2b197154..77ab878855c8 100644
--- a/lib/node_modules/@stdlib/stats/base/variancepn/lib/index.js
+++ b/lib/node_modules/@stdlib/stats/base/variancepn/lib/index.js
@@ -1,7 +1,7 @@
/**
* @license Apache-2.0
*
-* Copyright (c) 2020 The Stdlib Authors.
+* Copyright (c) 2025 The Stdlib Authors.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
@@ -27,22 +27,20 @@
* var variancepn = require( '@stdlib/stats/base/variancepn' );
*
* var x = [ 1.0, -2.0, 2.0 ];
-* var N = x.length;
*
-* var v = variancepn( N, 1, x, 1 );
+* var v = variancepn( x.length, 1, x, 1 );
* // returns ~4.3333
*
* @example
-* var floor = require( '@stdlib/math/base/special/floor' );
* var variancepn = require( '@stdlib/stats/base/variancepn' );
*
* var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ];
-* var N = floor( x.length / 2 );
*
-* var v = variancepn.ndarray( N, 1, x, 2, 1 );
+* var v = variancepn.ndarray( 4, 1, x, 2, 1 );
* // returns 6.25
*/
+
// MODULES //
var main = require( './main.js' );
diff --git a/lib/node_modules/@stdlib/stats/base/variancepn/lib/main.js b/lib/node_modules/@stdlib/stats/base/variancepn/lib/main.js
index f20dcbfda109..b19dbe83af19 100644
--- a/lib/node_modules/@stdlib/stats/base/variancepn/lib/main.js
+++ b/lib/node_modules/@stdlib/stats/base/variancepn/lib/main.js
@@ -1,7 +1,7 @@
/**
* @license Apache-2.0
*
-* Copyright (c) 2020 The Stdlib Authors.
+* Copyright (c) 2025 The Stdlib Authors.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
diff --git a/lib/node_modules/@stdlib/stats/base/variancepn/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/variancepn/lib/ndarray.js
index 6d3ee7b50e81..853ad02da4ce 100644
--- a/lib/node_modules/@stdlib/stats/base/variancepn/lib/ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/variancepn/lib/ndarray.js
@@ -21,6 +21,8 @@
// MODULES //
var gsumpw = require( '@stdlib/blas/ext/base/gsumpw' ).ndarray;
+var arraylike2object = require( '@stdlib/array/base/arraylike2object' );
+var accessors = require( './accessors.js' );
// MAIN //
@@ -40,20 +42,18 @@ var gsumpw = require( '@stdlib/blas/ext/base/gsumpw' ).ndarray;
* @param {PositiveInteger} N - number of indexed elements
* @param {number} correction - degrees of freedom adjustment
* @param {NumericArray} x - input array
-* @param {integer} stride - stride length
-* @param {NonNegativeInteger} offset - starting index
+* @param {integer} strideX - stride length for 'x'
+* @param {NonNegativeInteger} offsetX - starting index for 'x'
* @returns {number} variance
*
* @example
-* var floor = require( '@stdlib/math/base/special/floor' );
-*
* var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ];
-* var N = floor( x.length / 2 );
*
-* var v = variancepn( N, 1, x, 2, 1 );
+* var v = variancepn( 4, 1, x, 2, 1 );
* // returns 6.25
*/
-function variancepn( N, correction, x, stride, offset ) {
+function variancepn( N, correction, x, strideX, offsetX ) {
+ var ox;
var mu;
var ix;
var M2;
@@ -66,21 +66,27 @@ function variancepn( N, correction, x, stride, offset ) {
if ( N <= 0 || n <= 0.0 ) {
return NaN;
}
- if ( N === 1 || stride === 0 ) {
+ if ( N === 1 || strideX === 0 ) {
return 0.0;
}
+
+ ox = arraylike2object( x );
+ if ( ox.accessorProtocol) {
+ return accessors( N, correction, ox, strideX, offsetX);
+ }
+
// Compute an estimate for the mean:
- mu = gsumpw( N, x, stride, offset ) / N;
+ mu = gsumpw( N, x, strideX, offsetX ) / N;
// Compute the variance...
- ix = offset;
+ ix = offsetX;
M2 = 0.0;
M = 0.0;
for ( i = 0; i < N; i++ ) {
d = x[ ix ] - mu;
M2 += d * d;
M += d;
- ix += stride;
+ ix += strideX;
}
return (M2/n) - ((M/N)*(M/n));
}
diff --git a/lib/node_modules/@stdlib/stats/base/variancepn/lib/variancepn.js b/lib/node_modules/@stdlib/stats/base/variancepn/lib/variancepn.js
index e6be432823a1..a4d2616f6516 100644
--- a/lib/node_modules/@stdlib/stats/base/variancepn/lib/variancepn.js
+++ b/lib/node_modules/@stdlib/stats/base/variancepn/lib/variancepn.js
@@ -1,7 +1,7 @@
/**
* @license Apache-2.0
*
-* Copyright (c) 2020 The Stdlib Authors.
+* Copyright (c) 2025 The Stdlib Authors.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
@@ -20,7 +20,8 @@
// MODULES //
-var gsumpw = require( '@stdlib/blas/ext/base/gsumpw' );
+var stride2offset = require( '@stdlib/strided/base/stride2offset' );
+var ndarray = require( './ndarray.js' );
// MAIN //
@@ -40,7 +41,7 @@ var gsumpw = require( '@stdlib/blas/ext/base/gsumpw' );
* @param {PositiveInteger} N - number of indexed elements
* @param {number} correction - degrees of freedom adjustment
* @param {NumericArray} x - input array
-* @param {integer} stride - stride length
+* @param {integer} strideX - stride length for 'x'
* @returns {number} variance
*
* @example
@@ -50,40 +51,8 @@ var gsumpw = require( '@stdlib/blas/ext/base/gsumpw' );
* var v = variancepn( N, 1, x, 1 );
* // returns ~4.3333
*/
-function variancepn( N, correction, x, stride ) {
- var mu;
- var ix;
- var M2;
- var M;
- var d;
- var n;
- var i;
-
- n = N - correction;
- if ( N <= 0 || n <= 0.0 ) {
- return NaN;
- }
- if ( N === 1 || stride === 0 ) {
- return 0.0;
- }
- // Compute an estimate for the mean:
- mu = gsumpw( N, x, stride ) / N;
-
- if ( stride < 0 ) {
- ix = (1-N) * stride;
- } else {
- ix = 0;
- }
- // Compute the variance...
- M2 = 0.0;
- M = 0.0;
- for ( i = 0; i < N; i++ ) {
- d = x[ ix ] - mu;
- M2 += d * d;
- M += d;
- ix += stride;
- }
- return (M2/n) - ((M/N)*(M/n));
+function variancepn( N, correction, x, strideX ) {
+ return ndarray(N, correction, x, strideX, stride2offset(N, strideX));
}
diff --git a/lib/node_modules/@stdlib/stats/base/variancepn/test/test.js b/lib/node_modules/@stdlib/stats/base/variancepn/test/test.js
index 952358607ce1..06df5112b985 100644
--- a/lib/node_modules/@stdlib/stats/base/variancepn/test/test.js
+++ b/lib/node_modules/@stdlib/stats/base/variancepn/test/test.js
@@ -1,7 +1,7 @@
/**
* @license Apache-2.0
*
-* Copyright (c) 2020 The Stdlib Authors.
+* Copyright (c) 2025 The Stdlib Authors.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
diff --git a/lib/node_modules/@stdlib/stats/base/variancepn/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/variancepn/test/test.ndarray.js
index 0628463ab9a1..35341536fb08 100644
--- a/lib/node_modules/@stdlib/stats/base/variancepn/test/test.ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/variancepn/test/test.ndarray.js
@@ -1,7 +1,7 @@
/**
* @license Apache-2.0
*
-* Copyright (c) 2020 The Stdlib Authors.
+* Copyright (c) 2025 The Stdlib Authors.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
@@ -21,7 +21,7 @@
// MODULES //
var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
+var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' );
var isnan = require( '@stdlib/math/base/assert/is-nan' );
var variancepn = require( './../lib/ndarray.js' );
@@ -58,6 +58,25 @@ tape( 'the function calculates the population variance of a strided array', func
t.end();
});
+tape( 'the function calculates the population variance of a strided array (accessor)', function test( t ) {
+ var x;
+ var v;
+
+ x = [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ];
+ v = variancepn( x.length, 0, toAccessorArray(x), 1, 0 );
+ t.strictEqual( v, 53.5/x.length, 'returns expected value' );
+
+ x = [ -4.0, -4.0 ];
+ v = variancepn( x.length, 0, toAccessorArray(x), 1, 0 );
+ t.strictEqual( v, 0.0, 'returns expected value' );
+
+ x = [ NaN, 4.0 ];
+ v = variancepn( x.length, 0, toAccessorArray(x), 1, 0 );
+ t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+ t.end();
+});
+
tape( 'the function calculates the sample variance of a strided array', function test( t ) {
var x;
var v;
@@ -77,6 +96,25 @@ tape( 'the function calculates the sample variance of a strided array', function
t.end();
});
+tape( 'the function calculates the sample variance of a strided array (accessor)', function test( t ) {
+ var x;
+ var v;
+
+ x = [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ];
+ v = variancepn( x.length, 1, toAccessorArray(x), 1, 0 );
+ t.strictEqual( v, 53.5/(x.length-1), 'returns expected value' );
+
+ x = [ -4.0, -4.0 ];
+ v = variancepn( x.length, 1, toAccessorArray(x), 1, 0 );
+ t.strictEqual( v, 0.0, 'returns expected value' );
+
+ x = [ NaN, 4.0 ];
+ v = variancepn( x.length, 1, toAccessorArray(x), 1, 0 );
+ t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+ t.end();
+});
+
tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `NaN`', function test( t ) {
var x;
var v;
@@ -120,7 +158,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or
});
tape( 'the function supports a `stride` parameter', function test( t ) {
- var N;
var x;
var v;
@@ -135,15 +172,34 @@ tape( 'the function supports a `stride` parameter', function test( t ) {
2.0
];
- N = floor( x.length / 2 );
- v = variancepn( N, 1, x, 2, 0 );
+ v = variancepn( 4, 1, x, 2, 0 );
+
+ t.strictEqual( v, 6.25, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports a `stride` parameter (accessor)', function test( t ) {
+ var x;
+ var v;
+
+ x = [
+ 1.0, // 0
+ 2.0,
+ 2.0, // 1
+ -7.0,
+ -2.0, // 2
+ 3.0,
+ 4.0, // 3
+ 2.0
+ ];
+
+ v = variancepn( 4, 1, toAccessorArray(x), 2, 0 );
t.strictEqual( v, 6.25, 'returns expected value' );
t.end();
});
tape( 'the function supports a negative `stride` parameter', function test( t ) {
- var N;
var x;
var v;
@@ -158,8 +214,28 @@ tape( 'the function supports a negative `stride` parameter', function test( t )
2.0
];
- N = floor( x.length / 2 );
- v = variancepn( N, 1, x, -2, 6 );
+ v = variancepn( 4, 1, x, -2, 6 );
+
+ t.strictEqual( v, 6.25, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports a negative `stride` parameter (accessor)', function test( t ) {
+ var x;
+ var v;
+
+ x = [
+ 1.0, // 3
+ 2.0,
+ 2.0, // 2
+ -7.0,
+ -2.0, // 1
+ 3.0,
+ 4.0, // 0
+ 2.0
+ ];
+
+ v = variancepn( 4, 1, toAccessorArray(x), -2, 6 );
t.strictEqual( v, 6.25, 'returns expected value' );
t.end();
@@ -178,7 +254,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`',
});
tape( 'the function supports an `offset` parameter', function test( t ) {
- var N;
var x;
var v;
@@ -192,9 +267,29 @@ tape( 'the function supports an `offset` parameter', function test( t ) {
3.0,
4.0 // 3
];
- N = floor( x.length / 2 );
- v = variancepn( N, 1, x, 2, 1 );
+ v = variancepn( 4, 1, x, 2, 1 );
+ t.strictEqual( v, 6.25, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports an `offset` parameter (accessor)', function test( t ) {
+ var x;
+ var v;
+
+ x = [
+ 2.0,
+ 1.0, // 0
+ 2.0,
+ -2.0, // 1
+ -2.0,
+ 2.0, // 2
+ 3.0,
+ 4.0 // 3
+ ];
+
+ v = variancepn( 4, 1, toAccessorArray(x), 2, 1 );
t.strictEqual( v, 6.25, 'returns expected value' );
t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/variancepn/test/test.variancepn.js b/lib/node_modules/@stdlib/stats/base/variancepn/test/test.variancepn.js
index 5b72a7c7e5be..97ed107019f2 100644
--- a/lib/node_modules/@stdlib/stats/base/variancepn/test/test.variancepn.js
+++ b/lib/node_modules/@stdlib/stats/base/variancepn/test/test.variancepn.js
@@ -1,7 +1,7 @@
/**
* @license Apache-2.0
*
-* Copyright (c) 2020 The Stdlib Authors.
+* Copyright (c) 2025 The Stdlib Authors.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
@@ -21,10 +21,10 @@
// MODULES //
var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' );
var Float64Array = require( '@stdlib/array/float64' );
-var variancepn = require( './../lib/variancepn.js' );
+var variancepn = require( './../lib' );
// TESTS //
@@ -59,6 +59,25 @@ tape( 'the function calculates the population variance of a strided array', func
t.end();
});
+tape( 'the function calculates the population variance of a strided array (accessor)', function test( t ) {
+ var x;
+ var v;
+
+ x = [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ];
+ v = variancepn( x.length, 0, toAccessorArray(x), 1 );
+ t.strictEqual( v, 53.5/x.length, 'returns expected value' );
+
+ x = [ -4.0, -4.0 ];
+ v = variancepn( x.length, 0, toAccessorArray(x), 1 );
+ t.strictEqual( v, 0.0, 'returns expected value' );
+
+ x = [ NaN, 4.0 ];
+ v = variancepn( x.length, 0, toAccessorArray(x), 1 );
+ t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+ t.end();
+});
+
tape( 'the function calculates the sample variance of a strided array', function test( t ) {
var x;
var v;
@@ -78,6 +97,25 @@ tape( 'the function calculates the sample variance of a strided array', function
t.end();
});
+tape( 'the function calculates the sample variance of a strided array (accessor)', function test( t ) {
+ var x;
+ var v;
+
+ x = [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ];
+ v = variancepn( x.length, 1, toAccessorArray(x), 1 );
+ t.strictEqual( v, 53.5/(x.length-1), 'returns expected value' );
+
+ x = [ -4.0, -4.0 ];
+ v = variancepn( x.length, 1, toAccessorArray(x), 1 );
+ t.strictEqual( v, 0.0, 'returns expected value' );
+
+ x = [ NaN, 4.0 ];
+ v = variancepn( x.length, 1, toAccessorArray(x), 1 );
+ t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+ t.end();
+});
+
tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `NaN`', function test( t ) {
var x;
var v;
@@ -121,7 +159,6 @@ tape( 'if provided a `correction` parameter yielding `N-correction` less than or
});
tape( 'the function supports a `stride` parameter', function test( t ) {
- var N;
var x;
var v;
@@ -136,15 +173,34 @@ tape( 'the function supports a `stride` parameter', function test( t ) {
2.0
];
- N = floor( x.length / 2 );
- v = variancepn( N, 1, x, 2 );
+ v = variancepn( 4, 1, x, 2 );
+
+ t.strictEqual( v, 6.25, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports a `stride` parameter (accessor)', function test( t ) {
+ var x;
+ var v;
+
+ x = [
+ 1.0, // 0
+ 2.0,
+ 2.0, // 1
+ -7.0,
+ -2.0, // 2
+ 3.0,
+ 4.0, // 3
+ 2.0
+ ];
+
+ v = variancepn( 4, 1, toAccessorArray(x), 2 );
t.strictEqual( v, 6.25, 'returns expected value' );
t.end();
});
tape( 'the function supports a negative `stride` parameter', function test( t ) {
- var N;
var x;
var v;
@@ -159,8 +215,28 @@ tape( 'the function supports a negative `stride` parameter', function test( t )
2.0
];
- N = floor( x.length / 2 );
- v = variancepn( N, 1, x, -2 );
+ v = variancepn( 4, 1, x, -2 );
+
+ t.strictEqual( v, 6.25, 'returns expected value' );
+ t.end();
+});
+
+tape( 'the function supports a negative `stride` parameter (accessor)', function test( t ) {
+ var x;
+ var v;
+
+ x = [
+ 1.0, // 3
+ 2.0,
+ 2.0, // 2
+ -7.0,
+ -2.0, // 1
+ 3.0,
+ 4.0, // 0
+ 2.0
+ ];
+
+ v = variancepn( 4, 1, x, -2 );
t.strictEqual( v, 6.25, 'returns expected value' );
t.end();
@@ -181,7 +257,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`',
tape( 'the function supports view offsets', function test( t ) {
var x0;
var x1;
- var N;
var v;
x0 = new Float64Array([
@@ -197,9 +272,33 @@ tape( 'the function supports view offsets', function test( t ) {
]);
x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
- N = floor(x1.length / 2);
- v = variancepn( N, 1, x1, 2 );
+ v = variancepn( 4, 1, x1, 2 );
+ t.strictEqual( v, 6.25, 'returns expected value' );
+
+ t.end();
+});
+
+tape( 'the function supports view offsets (accessor)', function test( t ) {
+ var x0;
+ var x1;
+ var v;
+
+ x0 = new Float64Array([
+ 2.0,
+ 1.0, // 0
+ 2.0,
+ -2.0, // 1
+ -2.0,
+ 2.0, // 2
+ 3.0,
+ 4.0, // 3
+ 6.0
+ ]);
+
+ x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
+
+ v = variancepn( 4, 1, toAccessorArray(x1), 2 );
t.strictEqual( v, 6.25, 'returns expected value' );
t.end();