Press n or j to go to the next uncovered block, b, p or k for the previous block.
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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 max = require( '@stdlib/math/base/special/max' );
var min = require( '@stdlib/math/base/special/min' );
var sqrt = require( '@stdlib/math/base/special/sqrt' );
var rankData = require( './ranks.js' );
// MAIN //
/**
* Computes the Spearman rank correlation coefficient between `x` and `y`.
*
* @private
* @param {NumericArray} x - first data array
* @param {NumericArray} y - second data array
* @returns {Object} object containing the correlation coefficient and the ranks
*
* @example
* var x = [ 1.0, 2.0, 3.0, 4.0 ];
* var y = [ 1.0, 3.0, 2.0, 4.0 ];
* var out = scorr( x, y );
* // returns { rs: ~0.8, xRanks: [...], yRanks: [...] }
*/
function scorr( x, y ) {
var xRanks;
var yRanks;
var xmean;
var ymean;
var denom;
var num;
var out;
var xv;
var yv;
var n;
var i;
n = x.length;
// Compute ranks:
xRanks = rankData( x );
yRanks = rankData( y );
// Compute Pearson correlation on the ranks:
xmean = 0.0;
ymean = 0.0;
for ( i = 0; i < n; i++ ) {
xmean += xRanks[ i ];
ymean += yRanks[ i ];
}
xmean /= n;
ymean /= n;
num = 0.0;
xv = 0.0;
yv = 0.0;
for ( i = 0; i < n; i++ ) {
num += ( xRanks[ i ] - xmean ) * ( yRanks[ i ] - ymean );
xv += ( xRanks[ i ] - xmean ) * ( xRanks[ i ] - xmean );
yv += ( yRanks[ i ] - ymean ) * ( yRanks[ i ] - ymean );
}
denom = sqrt( xv ) * sqrt( yv );
out = {};
out.rs = ( denom === 0.0 ) ? 0.0 : max( min( num / denom, 1.0 ), -1.0 );
out.xRanks = xRanks;
out.yRanks = yRanks;
return out;
}
// EXPORTS //
module.exports = scorr;
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