mirror of
https://github.com/Karaka-Management/phpOMS.git
synced 2026-01-11 17:58:41 +00:00
Remove duplicate
This commit is contained in:
parent
80998b4813
commit
4366341ed9
|
|
@ -1,622 +0,0 @@
|
|||
<?php
|
||||
/**
|
||||
* Orange Management
|
||||
*
|
||||
* PHP Version 7.1
|
||||
*
|
||||
* @category TBD
|
||||
* @package TBD
|
||||
* @copyright Dennis Eichhorn
|
||||
* @license OMS License 1.0
|
||||
* @version 1.0.0
|
||||
* @link http://orange-management.com
|
||||
*/
|
||||
declare(strict_types=1);
|
||||
|
||||
namespace phpOMS\Business\Finance\Forecasting\ExponentialSmoothing;
|
||||
|
||||
use phpOMS\Business\Finance\Forecasting\SmoothingType;
|
||||
use phpOMS\Math\Statistic\Average;
|
||||
use phpOMS\Math\Statistic\Forecast\Error;
|
||||
|
||||
class ExponentialSmoothing
|
||||
{
|
||||
private $data = [];
|
||||
|
||||
private $errors = [];
|
||||
|
||||
private $rmse = 0.0;
|
||||
|
||||
private $mse = 0.0;
|
||||
|
||||
private $mae = 0.0;
|
||||
|
||||
private $sse = 0.0;
|
||||
|
||||
public function __construct(array $data)
|
||||
{
|
||||
$this->data = $data;
|
||||
}
|
||||
|
||||
public function getRMSE() : float
|
||||
{
|
||||
return $this->rmse;
|
||||
}
|
||||
|
||||
public function getMSE() : float
|
||||
{
|
||||
return $this->mse;
|
||||
}
|
||||
|
||||
public function getMAE() : float
|
||||
{
|
||||
return $this->mae;
|
||||
}
|
||||
|
||||
public function getSSE() : float
|
||||
{
|
||||
return $this->sse;
|
||||
}
|
||||
|
||||
public function getErrors() : array
|
||||
{
|
||||
return $this->errors;
|
||||
}
|
||||
|
||||
public function getForecast(int $future, int $trendType = TrendType::NONE, int $seasonalType = SeasonalType::NONE, int $cycle = 12, float $damping = 1) : array
|
||||
{
|
||||
$this->rmse = PHP_INT_MAX;
|
||||
|
||||
if($trendType === TrendType::ALL || $seasonalType === SeasonalType::ALL) {
|
||||
$trends = [$trendType];
|
||||
if($trendType === TrendType::ALL) {
|
||||
$trends = [TrendType::NONE, TrendType::ADDITIVE, TrendType::MULTIPLICATIVE];
|
||||
}
|
||||
|
||||
$seasonals = [$seasonalType];
|
||||
if($seasonalType === SeasonalType::ALL) {
|
||||
$seasonals = [SeasonalType::NONE, SeasonalType::ADDITIVE, SeasonalType::MULTIPLICATIVE];
|
||||
}
|
||||
|
||||
$forecast = [];
|
||||
$bestError = PHP_INT_MAX;
|
||||
foreach($trends as $trend) {
|
||||
foreach($seasonals as $seasonal) {
|
||||
$tempForecast = $this->getForecast($future, $trend, $seasonal, $cycle, $damping);
|
||||
|
||||
if ($this->rmse < $bestError) {
|
||||
$bestError = $this->rmse;
|
||||
$forecast = $tempForecast;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
return $forecast;
|
||||
} elseif($trendType === TrendType::NONE && $seasonalType === SeasonalType::NONE) {
|
||||
return $this->getNoneNone($future);
|
||||
} elseif($trendType === TrendType::NONE && $seasonalType === SeasonalType::ADDITIVE) {
|
||||
return $this->getNoneAdditive($future, $cycle);
|
||||
} elseif($trendType === TrendType::NONE && $seasonalType === SeasonalType::MULTIPLICATIVE) {
|
||||
return $this->getNoneMultiplicative($future, $cycle);
|
||||
} elseif($trendType === TrendType::ADDITIVE && $seasonalType === SeasonalType::NONE) {
|
||||
return $this->getAdditiveNone($future, $damping);
|
||||
} elseif($trendType === TrendType::ADDITIVE && $seasonalType === SeasonalType::ADDITIVE) {
|
||||
return $this->getAdditiveAdditive($future, $cycle, $damping);
|
||||
} elseif($trendType === TrendType::ADDITIVE && $seasonalType === SeasonalType::MULTIPLICATIVE) {
|
||||
return $this->getAdditiveMultiplicative($future, $cycle, $damping);
|
||||
} elseif($trendType === TrendType::MULTIPLICATIVE && $seasonalType === SeasonalType::NONE) {
|
||||
return $this->getMultiplicativeNone($future, $damping);
|
||||
} elseif($trendType === TrendType::MULTIPLICATIVE && $seasonalType === SeasonalType::ADDITIVE) {
|
||||
return $this->getMultiplicativeAdditive($future, $cycle, $damping);
|
||||
} elseif($trendType === TrendType::MULTIPLICATIVE && $seasonalType === SeasonalType::MULTIPLICATIVE) {
|
||||
return $this->getMultiplicativeMultiplicative($future, $cycle, $damping);
|
||||
}
|
||||
|
||||
throw new \Exception();
|
||||
}
|
||||
|
||||
private function dampingSum(float $damping, int $length) : float
|
||||
{
|
||||
if(abs($damping - 1) < 0.001) {
|
||||
return $length;
|
||||
}
|
||||
|
||||
$sum = 0;
|
||||
for($i = 0; $i < $length; $i++) {
|
||||
$sum += pow($damping, $i);
|
||||
}
|
||||
|
||||
return $sum;
|
||||
}
|
||||
|
||||
public function getNoneNone(int $future) : array
|
||||
{
|
||||
$level = [$this->data[0]];
|
||||
$dataLength = count($this->data) + $future;
|
||||
$forecast = [];
|
||||
|
||||
$alpha = 0.00;
|
||||
while ($alpha < 1) {
|
||||
$error = [];
|
||||
$tempForecast = [];
|
||||
|
||||
for($i = 1; $i < $dataLength; $i++) {
|
||||
$level[$i] = $alpha * ($i < $dataLength - $future ? $this->data[$i-1] : $tempForecast[$i-1]) + (1 - $alpha) * $level[$i-1];
|
||||
|
||||
$tempForecast[$i] = $level[$i];
|
||||
$error[] = $i < $dataLength - $future ? $this->data[$i] - $tempForecast[$i] : 0;
|
||||
}
|
||||
|
||||
$tempRMSE = Error::getRootMeanSquaredError($error);
|
||||
|
||||
if ($tempRMSE < $this->rmse) {
|
||||
$this->rmse = $tempRMSE;
|
||||
$forecast = $tempForecast;
|
||||
}
|
||||
|
||||
$alpha += 0.01;
|
||||
}
|
||||
|
||||
$this->errors = $error;
|
||||
$this->mse = Error::getMeanSquaredError($error);
|
||||
$this->mae = Error::getMeanAbsoulteError($error);
|
||||
$this->sse = Error::getSumSquaredError($error);
|
||||
|
||||
return $forecast;
|
||||
}
|
||||
|
||||
public function getNoneAdditive(int $future, int $cycle) : array
|
||||
{
|
||||
$level = [$this->data[0]];
|
||||
$dataLength = count($this->data) + $future;
|
||||
$forecast = [];
|
||||
$seasonal = [];
|
||||
|
||||
for($i = 1; $i < $cycle+1; $i++) {
|
||||
$seasonal[$i] = $this->data[$i-1] - $level[0];
|
||||
}
|
||||
|
||||
$alpha = 0.00;
|
||||
while ($alpha < 1) {
|
||||
$gamma = 0.00;
|
||||
|
||||
while($gamma < 1) {
|
||||
$gamma_ = $gamma * (1 - $alpha);
|
||||
$error = [];
|
||||
$tempForecast = [];
|
||||
|
||||
for($i = 1; $i < $dataLength; $i++) {
|
||||
$hm = (int) floor(($i-1) % $cycle) + 1;
|
||||
|
||||
$level[$i] = $alpha * (($i < $dataLength - $future ? $this->data[$i-1] : $tempForecast[$i-1]) - $seasonal[$i]) + (1 - $alpha) * $level[$i-1];
|
||||
$seasonal[$i+$cycle] = $gamma_*(($i < $dataLength - $future ? $this->data[$i-1] : $tempForecast[$i-1]) - $level[$i-1]) + (1 - $gamma_) * $seasonal[$i];
|
||||
|
||||
$tempForecast[$i] = $level[$i] + $seasonal[$i+$hm];
|
||||
$error[] = $i < $dataLength - $future ? $this->data[$i] - $tempForecast[$i] : 0;
|
||||
}
|
||||
|
||||
$tempRMSE = Error::getRootMeanSquaredError($error);
|
||||
|
||||
if ($tempRMSE < $this->rmse) {
|
||||
$this->rmse = $tempRMSE;
|
||||
$forecast = $tempForecast;
|
||||
}
|
||||
|
||||
$gamma += 0.01;
|
||||
}
|
||||
|
||||
$alpha += 0.01;
|
||||
}
|
||||
|
||||
$this->errors = $error;
|
||||
$this->mse = Error::getMeanSquaredError($error);
|
||||
$this->mae = Error::getMeanAbsoulteError($error);
|
||||
$this->sse = Error::getSumSquaredError($error);
|
||||
|
||||
return $forecast;
|
||||
}
|
||||
|
||||
public function getNoneMultiplicative(int $future, int $cycle) : array
|
||||
{
|
||||
$level = [$this->data[0]];
|
||||
$dataLength = count($this->data) + $future;
|
||||
$forecast = [];
|
||||
$seasonal = [];
|
||||
|
||||
for($i = 1; $i < $cycle+1; $i++) {
|
||||
$seasonal[$i] = $this->data[$i] / $level[0];
|
||||
}
|
||||
|
||||
$alpha = 0.00;
|
||||
while ($alpha < 1) {
|
||||
$gamma = 0.00;
|
||||
|
||||
while($gamma < 1) {
|
||||
$gamma_ = $gamma * (1 - $alpha);
|
||||
$error = [];
|
||||
$tempForecast = [];
|
||||
|
||||
for($i = 1; $i < $dataLength; $i++) {
|
||||
$hm = (int) floor(($i-1) % $cycle) + 1;
|
||||
|
||||
$level[$i] = $alpha * (($i < $dataLength - $future ? $this->data[$i-1] : $tempForecast[$i-1]) / $seasonal[$i]) + (1 - $alpha) * $level[$i-1];
|
||||
$seasonal[$i+$cycle] = $gamma_*(($i < $dataLength - $future ? $this->data[$i-1] : $tempForecast[$i-1]) / $level[$i-1]) + (1 - $gamma_) * $seasonal[$i];
|
||||
|
||||
$tempForecast[$i] = $level[$i] + $seasonal[$i+$hm];
|
||||
$error[] = $i < $dataLength - $future ? $this->data[$i] - $tempForecast[$i] : 0;
|
||||
}
|
||||
|
||||
$tempRMSE = Error::getRootMeanSquaredError($error);
|
||||
|
||||
if ($tempRMSE < $this->rmse) {
|
||||
$this->rmse = $tempRMSE;
|
||||
$forecast = $tempForecast;
|
||||
}
|
||||
|
||||
$gamma += 0.01;
|
||||
}
|
||||
|
||||
$alpha += 0.01;
|
||||
}
|
||||
|
||||
$this->errors = $error;
|
||||
$this->mse = Error::getMeanSquaredError($error);
|
||||
$this->mae = Error::getMeanAbsoulteError($error);
|
||||
$this->sse = Error::getSumSquaredError($error);
|
||||
|
||||
return $forecast;
|
||||
}
|
||||
|
||||
public function getAdditiveNone(int $future, float $damping) : array
|
||||
{
|
||||
$level = [$this->data[0]];
|
||||
$trend = [$this->data[1] - $this->data[0]];
|
||||
$dataLength = count($this->data) + $future;
|
||||
$forecast = [];
|
||||
|
||||
$alpha = 0.00;
|
||||
while ($alpha < 1) {
|
||||
$beta = 0.00;
|
||||
|
||||
while($beta < 1) {
|
||||
$error = [];
|
||||
$tempForecast = [];
|
||||
|
||||
for($i = 1; $i < $dataLength; $i++) {
|
||||
$level[$i] = $alpha * ($i < $dataLength - $future ? $this->data[$i-1] : $tempForecast[$i-1]) + (1 - $alpha) * ($level[$i-1] + $damping * $trend[$i-1]);
|
||||
$trend[$i] = $beta * ($level[$i] - $level[$i-1]) + (1 - $beta) * $damping * $trend[$i-1];
|
||||
|
||||
$tempForecast[$i] = $level[$i] + $this->dampingSum($damping, $i) * $trend[$i];
|
||||
$error[] = $i < $dataLength - $future ? $this->data[$i] - $tempForecast[$i] : 0;
|
||||
}
|
||||
|
||||
$tempRMSE = Error::getRootMeanSquaredError($error);
|
||||
|
||||
if ($tempRMSE < $this->rmse) {
|
||||
$this->rmse = $tempRMSE;
|
||||
$forecast = $tempForecast;
|
||||
}
|
||||
|
||||
$beta += 0.01;
|
||||
}
|
||||
|
||||
$alpha += 0.01;
|
||||
}
|
||||
|
||||
$this->errors = $error;
|
||||
$this->mse = Error::getMeanSquaredError($error);
|
||||
$this->mae = Error::getMeanAbsoulteError($error);
|
||||
$this->sse = Error::getSumSquaredError($error);
|
||||
|
||||
return $forecast;
|
||||
}
|
||||
|
||||
public function getAdditiveAdditive(int $future, int $cycle, float $damping) : array
|
||||
{
|
||||
$level = [1 / $cycle * array_sum(array_slice($this->data, 0, $cycle))];
|
||||
$trend = [1 / $cycle];
|
||||
$dataLength = count($this->data) + $future;
|
||||
$forecast = [];
|
||||
$seasonal = [];
|
||||
|
||||
$sum = 0;
|
||||
for($i = 1; $i < $cycle+1; $i++) {
|
||||
$sum += ($this->data[$cycle] - $this->data[$i]) / $cycle;
|
||||
}
|
||||
|
||||
$trend[0] *= $sum;
|
||||
|
||||
for($i = 1; $i < $cycle+1; $i++) {
|
||||
$seasonal[$i] = $this->data[$i-1] - $level[0];
|
||||
}
|
||||
|
||||
$alpha = 0.00;
|
||||
while ($alpha < 1) {
|
||||
$beta = 0.00;
|
||||
|
||||
while($beta < 1) {
|
||||
$gamma = 0.00;
|
||||
|
||||
while($gamma < 1) {
|
||||
$gamma_ = $gamma * (1 - $alpha);
|
||||
$error = [];
|
||||
$tempForecast = [];
|
||||
|
||||
for($i = 1; $i < $dataLength; $i++) {
|
||||
$hm = (int) floor(($i-1) % $cycle) + 1;
|
||||
|
||||
$level[$i] = $alpha * (($i < $dataLength - $future ? $this->data[$i-1] : $tempForecast[$i-1]) - $seasonal[$i]) + (1 - $alpha) * ($level[$i-1] + $damping * $trend[$i-1]);
|
||||
$trend[$i] = $beta * ($level[$i] - $level[$i-1]) + (1 - $beta) * $damping * $trend[$i-1];
|
||||
$seasonal[$i+$cycle] = $gamma_*(($i < $dataLength - $future ? $this->data[$i-1] : $tempForecast[$i-1]) - $level[$i-1]) + (1 - $gamma_) * $seasonal[$i];
|
||||
|
||||
$tempForecast[$i] = $level[$i] + $this->dampingSum($damping, $i) * $trend[$i] + $seasonal[$i+$hm];
|
||||
$error[] = $i < $dataLength - $future ? $this->data[$i] - $tempForecast[$i] : 0;
|
||||
}
|
||||
|
||||
$tempRMSE = Error::getRootMeanSquaredError($error);
|
||||
|
||||
if ($tempRMSE < $this->rmse) {
|
||||
$this->rmse = $tempRMSE;
|
||||
$forecast = $tempForecast;
|
||||
}
|
||||
|
||||
$gamma += 0.01;
|
||||
}
|
||||
|
||||
$beta += 0.01;
|
||||
}
|
||||
|
||||
$alpha += 0.01;
|
||||
}
|
||||
|
||||
$this->errors = $error;
|
||||
$this->mse = Error::getMeanSquaredError($error);
|
||||
$this->mae = Error::getMeanAbsoulteError($error);
|
||||
$this->sse = Error::getSumSquaredError($error);
|
||||
|
||||
return $forecast;
|
||||
}
|
||||
|
||||
public function getAdditiveMultiplicative(int $future, int $cycle, float $damping) : array
|
||||
{
|
||||
$level = [1 / $cycle * array_sum(array_slice($this->data, 0, $cycle))];
|
||||
$trend = [1 / $cycle];
|
||||
$dataLength = count($this->data) + $future;
|
||||
$forecast = [];
|
||||
$seasonal = [];
|
||||
$gamma_ = $gamma * (1 - $alpha);
|
||||
|
||||
$sum = 0;
|
||||
for($i = 1; $i < $cycle+1; $i++) {
|
||||
$sum += ($this->data[$cycle] - $this->data[$i]) / $cycle;
|
||||
}
|
||||
|
||||
$trend[0] *= $sum;
|
||||
|
||||
for($i = 1; $i < $cycle+1; $i++) {
|
||||
$seasonal[$i] = $this->data[$i] / $level[0];
|
||||
}
|
||||
|
||||
$alpha = 0.00;
|
||||
while ($alpha < 1) {
|
||||
$beta = 0.00;
|
||||
|
||||
while($beta < 1) {
|
||||
$gamma = 0.00;
|
||||
|
||||
while($gamma < 1) {
|
||||
$gamma_ = $gamma * (1 - $alpha);
|
||||
$error = [];
|
||||
$tempForecast = [];
|
||||
|
||||
for($i = 1; $i < $dataLength; $i++) {
|
||||
$hm = (int) floor(($i-1) % $cycle) + 1;
|
||||
|
||||
$level[$i] = $alpha * (($i < $dataLength - $future ? $this->data[$i-1] : $tempForecast[$i-1]) / $seasonal[$i]) + (1 - $alpha) * ($level[$i-1] + $damping * $trend[$i-1]);
|
||||
$trend[$i] = $beta * ($level[$i] - $level[$i-1]) + (1 - $beta) * $damping * $trend[$i-1];
|
||||
$seasonal[$i+$cycle] = $gamma_*($i < $dataLength - $future ? $this->data[$i-1] : $tempForecast[$i-1]) / ($level[$i-1] + $damping * $trend[$i-1]) + (1 - $gamma_) * $seasonal[$i];
|
||||
|
||||
$tempForecast[] = ($level[$i] + $this->dampingSum($damping, $i) * $trend[$i-1]) * $seasonal[$i+$hm];
|
||||
$error[] = $i < $dataLength - $future ? $this->data[$i] - $tempForecast[$i] : 0;
|
||||
}
|
||||
|
||||
$tempRMSE = Error::getRootMeanSquaredError($error);
|
||||
|
||||
if ($tempRMSE < $this->rmse) {
|
||||
$this->rmse = $tempRMSE;
|
||||
$forecast = $tempForecast;
|
||||
}
|
||||
|
||||
$gamma += 0.01;
|
||||
}
|
||||
|
||||
$beta += 0.01;
|
||||
}
|
||||
|
||||
$alpha += 0.01;
|
||||
}
|
||||
|
||||
$this->errors = $error;
|
||||
$this->mse = Error::getMeanSquaredError($error);
|
||||
$this->mae = Error::getMeanAbsoulteError($error);
|
||||
$this->sse = Error::getSumSquaredError($error);
|
||||
|
||||
return $forecast;
|
||||
}
|
||||
|
||||
public function getMultiplicativeNone(int $future, float $damping) : array
|
||||
{
|
||||
$level = [$this->data[0]];
|
||||
$trend = [$this->data[1] / $this->data[0]];
|
||||
$dataLength = count($this->data) + $future;
|
||||
$forecast = [];
|
||||
|
||||
$alpha = 0.00;
|
||||
while ($alpha < 1) {
|
||||
$beta = 0.00;
|
||||
|
||||
while($beta < 1) {
|
||||
$error = [];
|
||||
$tempForecast = [];
|
||||
|
||||
for($i = 1; $i < $dataLength; $i++) {
|
||||
$level[$i] = $alpha * ($i < $dataLength - $future ? $this->data[$i-1] : $tempForecast[$i-1]) + (1 - $alpha) * $level[$i-1] * pow($trend[$i-1], $damping);
|
||||
$trend[$i] = $beta * ($level[$i] / $level[$i-1]) + (1 - $beta) * pow($trend[$i-1], $damping);
|
||||
|
||||
$tempForecast[$i] = $level[$i] * pow($trend[$i], $this->dampingSum($damping, $i));
|
||||
$error[] = $i < $dataLength - $future ? $this->data[$i] - $tempForecast[$i] : 0;
|
||||
}
|
||||
|
||||
$tempRMSE = Error::getRootMeanSquaredError($error);
|
||||
|
||||
if ($tempRMSE < $this->rmse) {
|
||||
$this->rmse = $tempRMSE;
|
||||
$forecast = $tempForecast;
|
||||
}
|
||||
|
||||
$beta += 0.01;
|
||||
}
|
||||
$alpha += 0.01;
|
||||
}
|
||||
|
||||
$this->errors = $error;
|
||||
$this->mse = Error::getMeanSquaredError($error);
|
||||
$this->mae = Error::getMeanAbsoulteError($error);
|
||||
$this->sse = Error::getSumSquaredError($error);
|
||||
|
||||
return $forecast;
|
||||
}
|
||||
|
||||
public function getMultiplicativeAdditive(int $future, int $cycle, float $damping) : array
|
||||
{
|
||||
$level = [$this->data[0]];
|
||||
$trend = [1 / $cycle];
|
||||
$dataLength = count($this->data) + $future;
|
||||
$forecast = [];
|
||||
$seasonal = [];
|
||||
|
||||
$sum = 0;
|
||||
for($i = 1; $i < $cycle+1; $i++) {
|
||||
$sum += ($this->data[$cycle] - $this->data[$i]) / $cycle;
|
||||
}
|
||||
|
||||
$trend[0] *= $sum;
|
||||
|
||||
for($i = 1; $i < $cycle+1; $i++) {
|
||||
$seasonal[$i] = $this->data[$i-1] - $level[0];
|
||||
}
|
||||
|
||||
$alpha = 0.00;
|
||||
while ($alpha < 1) {
|
||||
$beta = 0.00;
|
||||
|
||||
while($beta < 1) {
|
||||
$gamma = 0.00;
|
||||
|
||||
while($gamma < 1) {
|
||||
$gamma_ = $gamma * (1 - $alpha);
|
||||
$error = [];
|
||||
$tempForecast = [];
|
||||
|
||||
for($i = 1; $i < $dataLength; $i++) {
|
||||
$hm = (int) floor(($i-1) % $cycle) + 1;
|
||||
|
||||
$level[$i] = $alpha * (($i < $dataLength - $future ? $this->data[$i-1] : $tempForecast[$i-1]) - $seasonal[$i]) + (1 - $alpha) * $level[$i-1] * pow($trend[$i-1], $damping);
|
||||
$trend[$i] = $beta * ($level[$i] / $level[$i-1]) + (1 - $beta) * pow($trend[$i-1], $damping);
|
||||
$seasonal[$i+$cycle] = $gamma_*(($i < $dataLength - $future ? $this->data[$i-1] : $tempForecast[$i-1]) - $level[$i-1] * pow($trend[$i-1], $damping)) + (1 - $gamma_) * $seasonal[$i];
|
||||
|
||||
$tempForecast[$i] = $level[$i] * pow($trend[$i], $this->dampingSum($damping, $i)) + $seasonal[$i+$hm];
|
||||
$error[] = $i < $dataLength - $future ? $this->data[$i] - $tempForecast[$i] : 0;
|
||||
}
|
||||
|
||||
$tempRMSE = Error::getRootMeanSquaredError($error);
|
||||
|
||||
if ($tempRMSE < $this->rmse) {
|
||||
$this->rmse = $tempRMSE;
|
||||
$forecast = $tempForecast;
|
||||
}
|
||||
|
||||
$gamma += 0.01;
|
||||
}
|
||||
|
||||
$beta += 0.01;
|
||||
}
|
||||
|
||||
$alpha += 0.01;
|
||||
}
|
||||
|
||||
$this->errors = $error;
|
||||
$this->mse = Error::getMeanSquaredError($error);
|
||||
$this->mae = Error::getMeanAbsoulteError($error);
|
||||
$this->sse = Error::getSumSquaredError($error);
|
||||
|
||||
return $forecast;
|
||||
}
|
||||
|
||||
public function getMultiplicativeMultiplicative(int $future, int $cycle, float $damping) : array
|
||||
{
|
||||
$level = [$this->data[0]];
|
||||
$trend = [1 / $cycle];
|
||||
$dataLength = count($this->data) + $future;
|
||||
$forecast = [];
|
||||
$seasonal = [];
|
||||
|
||||
$sum = 0;
|
||||
for($i = 1; $i < $cycle+1; $i++) {
|
||||
$sum += ($this->data[$cycle] - $this->data[$i]) / $cycle;
|
||||
}
|
||||
|
||||
$trend[0] *= $sum;
|
||||
|
||||
for($i = 1; $i < $cycle+1; $i++) {
|
||||
$seasonal[$i] = $this->data[$i] / $level[0];
|
||||
}
|
||||
|
||||
$alpha = 0.00;
|
||||
while ($alpha < 1) {
|
||||
$beta = 0.00;
|
||||
|
||||
while($beta < 1) {
|
||||
$gamma = 0.00;
|
||||
|
||||
while($gamma < 1) {
|
||||
$gamma_ = $gamma * (1 - $alpha);
|
||||
$error = [];
|
||||
$tempForecast = [];
|
||||
|
||||
for($i = 1; $i < $dataLength; $i++) {
|
||||
$hm = (int) floor(($i-1) % $cycle) + 1;
|
||||
|
||||
$level[$i] = $alpha * (($i < $dataLength - $future ? $this->data[$i-1] : $tempForecast[$i-1]) / $seasonal[$i]) + (1 - $alpha) * $level[$i-1] * pow($trend[$i-1], $damping);
|
||||
$trend[$i] = $beta * ($level[$i] / $level[$i-1]) + (1 - $beta) * pow($trend[$i-1], $damping);
|
||||
$seasonal[$i+$cycle] = $gamma_*($i < $dataLength - $future ? $this->data[$i-1] : $tempForecast[$i-1]) / ($level[$i-1] * pow($trend[$i-1], $damping)) + (1 - $gamma_) * $seasonal[$i];
|
||||
|
||||
$tempForecast[$i] = $level[$i] * pow($trend[$i], $this->dampingSum($damping, $i)) * $seasonal[$i+$hm];
|
||||
$error[] = $i < $dataLength - $future ? $this->data[$i] - $tempForecast[$i] : 0;
|
||||
}
|
||||
|
||||
$tempRMSE = Error::getRootMeanSquaredError($error);
|
||||
|
||||
if ($tempRMSE < $this->rmse) {
|
||||
$this->rmse = $tempRMSE;
|
||||
$forecast = $tempForecast;
|
||||
}
|
||||
|
||||
$gamma += 0.01;
|
||||
}
|
||||
|
||||
$beta += 0.01;
|
||||
}
|
||||
|
||||
$alpha += 0.01;
|
||||
}
|
||||
|
||||
$this->errors = $error;
|
||||
$this->mse = Error::getMeanSquaredError($error);
|
||||
$this->mae = Error::getMeanAbsoulteError($error);
|
||||
$this->sse = Error::getSumSquaredError($error);
|
||||
|
||||
return $forecast;
|
||||
}
|
||||
|
||||
}
|
||||
Loading…
Reference in New Issue
Block a user