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Differences Between: [Versions 310 and 400] [Versions 310 and 401] [Versions 310 and 402] [Versions 310 and 403]

   1  <?php
   2  
   3  declare(strict_types=1);
   4  
   5  namespace Phpml\Math\Statistic;
   6  
   7  use Phpml\Exception\InvalidArgumentException;
   8  
   9  /**
  10   * Analysis of variance
  11   * https://en.wikipedia.org/wiki/Analysis_of_variance
  12   */
  13  final class ANOVA
  14  {
  15      /**
  16       * The one-way ANOVA tests the null hypothesis that 2 or more groups have
  17       * the same population mean. The test is applied to samples from two or
  18       * more groups, possibly with differing sizes.
  19       *
  20       * @param array[] $samples - each row is class samples
  21       *
  22       * @return float[]
  23       */
  24      public static function oneWayF(array $samples): array
  25      {
  26          $classes = count($samples);
  27          if ($classes < 2) {
  28              throw new InvalidArgumentException('The array must have at least 2 elements');
  29          }
  30  
  31          $samplesPerClass = array_map(function (array $class): int {
  32              return count($class);
  33          }, $samples);
  34          $allSamples = (int) array_sum($samplesPerClass);
  35          $ssAllSamples = self::sumOfSquaresPerFeature($samples);
  36          $sumSamples = self::sumOfFeaturesPerClass($samples);
  37          $squareSumSamples = self::sumOfSquares($sumSamples);
  38          $sumSamplesSquare = self::squaresSum($sumSamples);
  39          $ssbn = self::calculateSsbn($samples, $sumSamplesSquare, $samplesPerClass, $squareSumSamples, $allSamples);
  40          $sswn = self::calculateSswn($ssbn, $ssAllSamples, $squareSumSamples, $allSamples);
  41          $dfbn = $classes - 1;
  42          $dfwn = $allSamples - $classes;
  43  
  44          $msb = array_map(function ($s) use ($dfbn) {
  45              return $s / $dfbn;
  46          }, $ssbn);
  47          $msw = array_map(function ($s) use ($dfwn) {
  48              return $s / $dfwn;
  49          }, $sswn);
  50  
  51          $f = [];
  52          foreach ($msb as $index => $msbValue) {
  53              $f[$index] = $msbValue / $msw[$index];
  54          }
  55  
  56          return $f;
  57      }
  58  
  59      private static function sumOfSquaresPerFeature(array $samples): array
  60      {
  61          $sum = array_fill(0, count($samples[0][0]), 0);
  62          foreach ($samples as $class) {
  63              foreach ($class as $sample) {
  64                  foreach ($sample as $index => $feature) {
  65                      $sum[$index] += $feature ** 2;
  66                  }
  67              }
  68          }
  69  
  70          return $sum;
  71      }
  72  
  73      private static function sumOfFeaturesPerClass(array $samples): array
  74      {
  75          return array_map(function (array $class) {
  76              $sum = array_fill(0, count($class[0]), 0);
  77              foreach ($class as $sample) {
  78                  foreach ($sample as $index => $feature) {
  79                      $sum[$index] += $feature;
  80                  }
  81              }
  82  
  83              return $sum;
  84          }, $samples);
  85      }
  86  
  87      private static function sumOfSquares(array $sums): array
  88      {
  89          $squares = array_fill(0, count($sums[0]), 0);
  90          foreach ($sums as $row) {
  91              foreach ($row as $index => $sum) {
  92                  $squares[$index] += $sum;
  93              }
  94          }
  95  
  96          return array_map(function ($sum) {
  97              return $sum ** 2;
  98          }, $squares);
  99      }
 100  
 101      private static function squaresSum(array $sums): array
 102      {
 103          foreach ($sums as &$row) {
 104              foreach ($row as &$sum) {
 105                  $sum **= 2;
 106              }
 107          }
 108  
 109          return $sums;
 110      }
 111  
 112      private static function calculateSsbn(array $samples, array $sumSamplesSquare, array $samplesPerClass, array $squareSumSamples, int $allSamples): array
 113      {
 114          $ssbn = array_fill(0, count($samples[0][0]), 0);
 115          foreach ($sumSamplesSquare as $classIndex => $class) {
 116              foreach ($class as $index => $feature) {
 117                  $ssbn[$index] += $feature / $samplesPerClass[$classIndex];
 118              }
 119          }
 120  
 121          foreach ($squareSumSamples as $index => $sum) {
 122              $ssbn[$index] -= $sum / $allSamples;
 123          }
 124  
 125          return $ssbn;
 126      }
 127  
 128      private static function calculateSswn(array $ssbn, array $ssAllSamples, array $squareSumSamples, int $allSamples): array
 129      {
 130          $sswn = [];
 131          foreach ($ssAllSamples as $index => $ss) {
 132              $sswn[$index] = ($ss - $squareSumSamples[$index] / $allSamples) - $ssbn[$index];
 133          }
 134  
 135          return $sswn;
 136      }
 137  }