added accessor array

Author: thedeeppp

lib/node_modules/@stdlib/stats/base/variancech/lib/accessors.js

@@ -0,0 +1,67 @@
+/**
+* @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';
+
+// MAIN //
+
+/**
+* Computes the variance of a strided array using a one-pass trial mean algorithm.
+*
+* @param {PositiveInteger} N - number of indexed elements
+* @param {number} correction - degrees of freedom adjustment
+* @param {Object} x - input array object
+* @param {Function} x.get - accessor function
+* @param {integer} stride - stride length
+* @param {NonNegativeInteger} offset - starting index
+* @returns {number} variance
+*/
+function variancech(N, correction, x, stride, offset) {
+    var sum;
+    var ix;
+    var i;
+
+    if (N <= 0) {
+        return NaN;
+    }
+    if (N === 1 || stride === 0) {
+        return 0.0;
+    }
+    ix = offset;
+    sum = 0.0;
+
+    // Calculate mean
+    for (i = 0; i < N; i++) {
+        sum += x.get(ix);
+        ix += stride;
+    }
+    var mean = sum / N;
+
+    // Calculate variance
+    ix = offset;
+    var sum2 = 0.0;
+    for (i = 0; i < N; i++) {
+        var delta = x.get(ix) - mean;
+        sum2 += delta * delta;
+        ix += stride;
+    }
+    return sum2 / (N - correction);
+}
+
+// EXPORTS //
+module.exports = variancech; 

lib/node_modules/@stdlib/stats/base/variancech/lib/index.js

@@ -45,11 +45,10 @@
 
 // MODULES //
 
-var main = require( './main.js' );
-
+var main = require('./main.js');
+var ndarray = require('./ndarray.js');
 
 // EXPORTS //
 
 module.exports = main;
-
-// exports: { "ndarray": "main.ndarray" }
+module.exports.ndarray = ndarray;

lib/node_modules/@stdlib/stats/base/variancech/lib/main.js

@@ -29,6 +29,25 @@ var ndarray = require( './ndarray.js' );
 
 setReadOnly( variancech, 'ndarray', ndarray );
 
+/**
+* Computes the variance of a strided array using a one-pass trial mean algorithm.
+*
+* @param {PositiveInteger} N - number of indexed elements
+* @param {number} correction - degrees of freedom adjustment
+* @param {NumericArray} x - input array
+* @param {integer} stride - stride length
+* @returns {number} variance
+*
+* @example
+* var x = [ 1.0, -2.0, 2.0 ];
+*
+* var v = variancech( x.length, 1, x, 1 );
+* // returns ~4.3333
+*/
+
+function variancech(N, correction, x, stride) {
+    return ndarray(N, correction, x, stride, 0);
+}
 
 // EXPORTS //
 

lib/node_modules/@stdlib/stats/base/variancech/lib/ndarray.js

@@ -18,8 +18,11 @@
 
 'use strict';
 
-// MAIN //
+// MODULES //
+var isAccessorArray = require('@stdlib/array/base/assert/is-accessor-array');
+var accessors = require('./accessors.js');
 
+// MAIN //
 /**
 * Computes the variance of a strided array using a one-pass trial mean algorithm.
 *
@@ -50,7 +53,10 @@
 * var v = variancech( N, 1, x, 2, 1 );
 * // returns 6.25
 */
-function variancech( N, correction, x, stride, offset ) {
+function variancech(N, correction, x, stride, offset) {
+	if (isAccessorArray(x)) {
+		return accessors(N, correction, x, stride, offset);
+	}
 	var mu;
 	var ix;
 	var M2;