MathPHP\Statistics\Average::median PHP Метод

    public static function median(array $numbers)
    {
        if (empty($numbers)) {
            return null;
        }
        // Reset the array key indexes because we don't know what might be passed in
        $numbers = array_values($numbers);
        // For odd number of numbers, take the middle indexed number
        if (count($numbers) % 2 == 1) {
            $middle_index = intdiv(count($numbers), 2);
            return self::kthSmallest($numbers, $middle_index);
        }
        // For even number of items, take the mean of the middle two indexed numbers
        $left_middle_index = intdiv(count($numbers), 2) - 1;
        $left_median = self::kthSmallest($numbers, $left_middle_index);
        $right_middle_index = $left_middle_index + 1;
        $right_median = self::kthSmallest($numbers, $right_middle_index);
        return self::mean([$left_median, $right_median]);
    }

 /**
  * Calculate the regression parameters using the Theil-Sen method
  *
  * Procedure:
  * Calculate the slopes of all pairs of points and select the median value
  * Calculate the intercept using the slope, and the medians of the X and Y values.
  *   b = Ymedian - (m * Xmedian)
  */
 public function calculate()
 {
     // The slopes array will be a list of slopes between all pairs of points
     $slopes = [];
     $n = count($this->points);
     for ($i = 0; $i < $n; $i++) {
         for ($j = $i + 1; $j < $n; $j++) {
             $pointi = $this->points[$i];
             $pointj = $this->points[$j];
             $slopes[] = ($pointj[1] - $pointi[1]) / ($pointj[0] - $pointi[0]);
         }
     }
     $this->m = Average::median($slopes);
     $this->b = Average::median($this->ys) - $this->m * Average::median($this->xs);
     $this->parameters = [$this->b, $this->m];
 }