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| 1 | <?php |
| 2 | /** |
| 3 | * Jingga |
| 4 | * |
| 5 | * PHP Version 8.1 |
| 6 | * |
| 7 | * @package phpOMS\Math\Statistic\Forecast |
| 8 | * @copyright Dennis Eichhorn |
| 9 | * @license OMS License 2.0 |
| 10 | * @version 1.0.0 |
| 11 | * @link https://jingga.app |
| 12 | */ |
| 13 | declare(strict_types=1); |
| 14 | |
| 15 | namespace phpOMS\Math\Statistic\Forecast; |
| 16 | |
| 17 | /** |
| 18 | * General forecasts helper class. |
| 19 | * |
| 20 | * @package phpOMS\Math\Statistic\Forecast |
| 21 | * @license OMS License 2.0 |
| 22 | * @link https://jingga.app |
| 23 | * @since 1.0.0 |
| 24 | */ |
| 25 | final class Forecasts |
| 26 | { |
| 27 | /** |
| 28 | * Get forecast/prediction interval. |
| 29 | * |
| 30 | * @param float $forecast Forecast value |
| 31 | * @param float $standardDeviation Standard Deviation of forecast |
| 32 | * @param float $interval Forecast multiplier for prediction intervals |
| 33 | * |
| 34 | * @return array<int|float> |
| 35 | * |
| 36 | * @since 1.0.0 |
| 37 | */ |
| 38 | public static function getForecastInteval(float $forecast, float $standardDeviation, float $interval = 1.96) : array |
| 39 | { |
| 40 | return [$forecast - $interval * $standardDeviation, $forecast + $interval * $standardDeviation]; |
| 41 | } |
| 42 | |
| 43 | /** |
| 44 | * Simple seasonal forecast. |
| 45 | * |
| 46 | * @param array<int|float> $history History |
| 47 | * @param int $periods Number of periods to forecast |
| 48 | * @param int $seasonality Seasonality |
| 49 | * |
| 50 | * @return array<int|float> |
| 51 | * |
| 52 | * @since 1.0.0 |
| 53 | */ |
| 54 | public static function simpleSeasonalForecast(array $history, int $periods, int $seasonality = 1) : array |
| 55 | { |
| 56 | $size = \count($history); |
| 57 | $avg = \array_sum($history) / $size; |
| 58 | |
| 59 | $variance = 0; |
| 60 | foreach ($history as $sale) { |
| 61 | $variance += \pow($sale - $avg, 2); |
| 62 | } |
| 63 | |
| 64 | $variance /= $size; |
| 65 | $stdDeviation = \sqrt($variance); |
| 66 | |
| 67 | // Calculate the seasonal index for each period |
| 68 | $seasonalIndex = []; |
| 69 | for ($i = 0; $i < $seasonality; ++$i) { |
| 70 | $seasonalIndex[$i] = 0; |
| 71 | $count = 0; |
| 72 | |
| 73 | for ($j = $i; $j < $size; $j += $seasonality) { |
| 74 | $seasonalIndex[$i] += $history[$j]; |
| 75 | ++$count; |
| 76 | } |
| 77 | |
| 78 | if ($count > 0) { |
| 79 | $seasonalIndex[$i] /= $count; |
| 80 | $seasonalIndex[$i] /= $avg; |
| 81 | } |
| 82 | } |
| 83 | |
| 84 | // Forecast the next periods |
| 85 | $forecast = []; |
| 86 | for ($i = 1; $i <= $periods; ++$i) { |
| 87 | $seasonalMultiplier = $seasonalIndex[($i - 1) % $seasonality]; |
| 88 | $forecast[] = $avg * $seasonalMultiplier + ($stdDeviation * $i); |
| 89 | } |
| 90 | |
| 91 | return $forecast; |
| 92 | } |
| 93 | } |