time-to-botec/squiggle/node_modules/@stdlib/stats/incr/kurtosis/lib/main.js
NunoSempere b6addc7f05 feat: add the node modules
Necessary in order to clearly see the squiggle hotwiring.
2022-12-03 12:44:49 +00:00

137 lines
3.3 KiB
JavaScript
Raw Blame History

This file contains ambiguous Unicode characters

This file contains Unicode characters that might be confused with other characters. If you think that this is intentional, you can safely ignore this warning. Use the Escape button to reveal them.

/**
* @license Apache-2.0
*
* Copyright (c) 2018 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 isnan = require( '@stdlib/math/base/assert/is-nan' );
// MAIN //
/**
* Returns an accumulator function which incrementally computes a corrected sample excess kurtosis.
*
* ## Method
*
* The algorithm computes the sample excess kurtosis using the formula for `G_2` in [Joanes and Gill 1998][@joanes:1998]. In contrast to alternatives for calculating a sample kurtosis, `G_2` is an unbiased estimator under normality.
*
* ## References
*
* - Joanes, D. N., and C. A. Gill. 1998. "Comparing measures of sample skewness and kurtosis." _Journal of the Royal Statistical Society: Series D (The Statistician)_ 47 (1). Blackwell Publishers Ltd: 18389. doi:[10.1111/1467-9884.00122][@joanes:1998].
*
* [@joanes:1998]: http://dx.doi.org/10.1111/1467-9884.00122
*
* @returns {Function} accumulator function
*
* @example
* var accumulator = incrkurtosis();
*
* var kurtosis = accumulator();
* // returns null
*
* kurtosis = accumulator( 2.0 );
* // returns null
*
* kurtosis = accumulator( 2.0 );
* // returns null
*
* kurtosis = accumulator( -4.0 );
* // returns null
*
* kurtosis = accumulator( -4.0 );
* // returns -6.0
*/
function incrkurtosis() {
var deltaN2;
var deltaN;
var delta;
var term1;
var mean;
var tmp;
var g2;
var M2;
var M3;
var M4;
var N;
deltaN2 = 0.0;
deltaN = 0.0;
delta = 0.0;
term1 = 0.0;
mean = 0.0;
M2 = 0.0;
M3 = 0.0;
M4 = 0.0;
N = 0;
return accumulator;
/**
* If provided a value, the accumulator function returns an updated corrected sample excess kurtosis. If not provided a value, the accumulator function returns the current corrected sample excess kurtosis.
*
* @private
* @param {number} [x] - new value
* @returns {(number|null)} corrected sample excess kurtosis
*/
function accumulator( x ) {
if ( arguments.length === 0 ) {
if ( N < 4 ) {
return ( isnan( M4 ) ) ? NaN : null;
}
// Calculate the population excess kurtosis:
g2 = (( N*M4 ) / ( M2*M2 )) - 3.0;
// Return the corrected sample excess kurtosis:
return (N-1) / ( (N-2)*(N-3) ) * ( ((N+1)*g2) + 6.0 );
}
N += 1;
delta = x - mean;
deltaN = delta / N;
deltaN2 = deltaN * deltaN;
term1 = delta * deltaN * (N-1);
tmp = term1 * deltaN2 * ((N*N) - (3*N) + 3);
tmp += 6.0 * deltaN2 * M2;
tmp -= 4.0 * deltaN * M3;
M4 += tmp;
tmp = term1 * deltaN * (N-2);
tmp -= 3.0 * deltaN * M2;
M3 += tmp;
M2 += term1;
mean += deltaN;
if ( N < 4 ) {
return ( isnan( M4 ) ) ? NaN : null;
}
// Calculate the population excess kurtosis:
g2 = (N*M4 / ( M2*M2 )) - 3.0;
// Return the corrected sample excess kurtosis:
return (N-1) / ( (N-2)*(N-3) ) * ( ((N+1)*g2) + 6.0 );
}
}
// EXPORTS //
module.exports = incrkurtosis;