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See Release Notes

  • Bug fixes for general core bugs in 3.10.x will end 8 November 2021 (12 months).
  • Bug fixes for security issues in 3.10.x will end 9 May 2022 (18 months).
  • PHP version: minimum PHP 7.2.0 Note: minimum PHP version has increased since Moodle 3.8. PHP 7.3.x and 7.4.x are supported too.
<?php

declare(strict_types=1);

namespace Phpml\Math\Statistic;

use Phpml\Exception\InvalidArgumentException;

/**
 * Analysis of variance
 * https://en.wikipedia.org/wiki/Analysis_of_variance
 */
final class ANOVA
{
    /**
     * The one-way ANOVA tests the null hypothesis that 2 or more groups have
     * the same population mean. The test is applied to samples from two or
     * more groups, possibly with differing sizes.
     *
     * @param array[] $samples - each row is class samples
     *
     * @return float[]
     */
    public static function oneWayF(array $samples): array
    {
        $classes = count($samples);
        if ($classes < 2) {
            throw new InvalidArgumentException('The array must have at least 2 elements');
        }

< $samplesPerClass = array_map(function (array $class): int {
> $samplesPerClass = array_map(static function (array $class): int {
return count($class); }, $samples); $allSamples = (int) array_sum($samplesPerClass); $ssAllSamples = self::sumOfSquaresPerFeature($samples); $sumSamples = self::sumOfFeaturesPerClass($samples); $squareSumSamples = self::sumOfSquares($sumSamples); $sumSamplesSquare = self::squaresSum($sumSamples); $ssbn = self::calculateSsbn($samples, $sumSamplesSquare, $samplesPerClass, $squareSumSamples, $allSamples); $sswn = self::calculateSswn($ssbn, $ssAllSamples, $squareSumSamples, $allSamples); $dfbn = $classes - 1; $dfwn = $allSamples - $classes;
< $msb = array_map(function ($s) use ($dfbn) {
> $msb = array_map(static function ($s) use ($dfbn) {
return $s / $dfbn; }, $ssbn);
< $msw = array_map(function ($s) use ($dfwn) {
> $msw = array_map(static function ($s) use ($dfwn) { > if ($dfwn === 0) { > return 1; > } >
return $s / $dfwn; }, $sswn); $f = []; foreach ($msb as $index => $msbValue) { $f[$index] = $msbValue / $msw[$index]; } return $f; } private static function sumOfSquaresPerFeature(array $samples): array { $sum = array_fill(0, count($samples[0][0]), 0); foreach ($samples as $class) { foreach ($class as $sample) { foreach ($sample as $index => $feature) { $sum[$index] += $feature ** 2; } } } return $sum; } private static function sumOfFeaturesPerClass(array $samples): array {
< return array_map(function (array $class) {
> return array_map(static function (array $class): array {
$sum = array_fill(0, count($class[0]), 0); foreach ($class as $sample) { foreach ($sample as $index => $feature) { $sum[$index] += $feature; } } return $sum; }, $samples); } private static function sumOfSquares(array $sums): array { $squares = array_fill(0, count($sums[0]), 0); foreach ($sums as $row) { foreach ($row as $index => $sum) { $squares[$index] += $sum; } }
< return array_map(function ($sum) {
> return array_map(static function ($sum) {
return $sum ** 2; }, $squares); } private static function squaresSum(array $sums): array { foreach ($sums as &$row) { foreach ($row as &$sum) { $sum **= 2; } } return $sums; } private static function calculateSsbn(array $samples, array $sumSamplesSquare, array $samplesPerClass, array $squareSumSamples, int $allSamples): array { $ssbn = array_fill(0, count($samples[0][0]), 0); foreach ($sumSamplesSquare as $classIndex => $class) { foreach ($class as $index => $feature) { $ssbn[$index] += $feature / $samplesPerClass[$classIndex]; } } foreach ($squareSumSamples as $index => $sum) { $ssbn[$index] -= $sum / $allSamples; } return $ssbn; } private static function calculateSswn(array $ssbn, array $ssAllSamples, array $squareSumSamples, int $allSamples): array { $sswn = []; foreach ($ssAllSamples as $index => $ss) { $sswn[$index] = ($ss - $squareSumSamples[$index] / $allSamples) - $ssbn[$index]; } return $sswn; } }