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* @license Apache-2.0
*
* Copyright (c) 2026 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 numelDimension = require( '@stdlib/ndarray/base/numel-dimension' );
var getStride = require( '@stdlib/ndarray/base/stride' );
var getOffset = require( '@stdlib/ndarray/base/offset' );
var getData = require( '@stdlib/ndarray/base/data-buffer' );
var isnan = require( '@stdlib/math/base/assert/is-nan' );
// MAIN //
/**
* Computes the sample variance of a one-dimensional ndarray, ignoring `NaN` values.
*
* @param {ArrayLikeObject<Object>} arrays - array-like object containing an input ndarray
* @param {number} correction - degrees of freedom adjustment
* @returns {number} sample variance
*/
function snanvariance( arrays, correction ) {
var stride;
var offset;
var sumsq;
var count;
var data;
var mean;
var ix;
var x;
var N;
var i;
var v;
x = arrays[ 0 ];
N = numelDimension( x, 0 );
data = getData( x );
stride = getStride( x, 0 );
offset = getOffset( x );
mean = 0.0;
sumsq = 0.0;
count = 0;
// First pass: compute mean of non-NaN values:
ix = offset;
for ( i = 0; i < N; i++ ) {
v = data[ ix ];
if ( !isnan( v ) ) {
mean += v;
count += 1;
}
ix += stride;
}
if ( count - correction <= 0 ) {
return NaN;
}
mean /= count;
// Second pass: compute squared deviations:
ix = offset;
for ( i = 0; i < N; i++ ) {
v = data[ ix ];
if ( !isnan( v ) ) {
v -= mean;
sumsq += v * v;
}
ix += stride;
}
return sumsq / ( count - correction );
}
// EXPORTS //
module.exports = snanvariance;
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