/**
* __construct Function
*
* Constructor function for this regression model. Takes two arrays
* of data that are parallel arrays of independent and dependent
* observations.
*
* @param array $datax The series of independent variables
* @param array $datay The series of dependent variables
* @return LogarithmicRegression An object representing the regression model
*/
public function __construct($datax, $datay)
{
$logx = array();
foreach ($datax as $x) {
$logx[] = log($x);
}
$this->r = \PHPStats\Stats::correlation($logx, $datay);
$this->beta = \PHPStats\Stats::covariance($logx, $datay) / \PHPStats\Stats::variance($logx);
$this->alpha = \PHPStats\Stats::average($datay) - $this->beta * \PHPStats\Stats::average($logx);
}
/**
* __construct Function
*
* Constructor function for this regression model. Takes two arrays
* of data that are parallel arrays of independent and dependent
* observations.
*
* @param array $datax The series of independent variables
* @param array $datay The series of dependent variables
* @return ExponentialRegression An object representing the regression model
*/
public function __construct(array $datax, array $datay)
{
$logy = array();
foreach ($datay as $y) {
$logy[] = log($y);
}
$this->r = \PHPStats\Stats::correlation($datax, $logy);
$logbeta = \PHPStats\Stats::covariance($datax, $logy) / \PHPStats\Stats::variance($datax);
$logalpha = \PHPStats\Stats::average($logy) - $logbeta * \PHPStats\Stats::average($datax);
$this->beta = exp($logbeta);
$this->alpha = exp($logalpha);
}
/**
* __construct Function
*
* Constructor function for this regression model. Takes two arrays
* of data that are parallel arrays of independent and dependent
* observations.
*
* @param array $datax The series of independent variables
* @param array $datay The series of dependent variables
* @return LinearRegression An object representing the regression model
*/
public function __construct(array $datax, array $datay)
{
$this->beta = \PHPStats\Stats::covariance($datax, $datay) / \PHPStats\Stats::variance($datax);
$this->alpha = \PHPStats\Stats::average($datay) - $this->beta * \PHPStats\Stats::average($datax);
$this->r = \PHPStats\Stats::correlation($datax, $datay);
}
public function test_variance()
{
$this->assertEquals(2, Stats::variance($this->datax));
$this->assertEquals(2, Stats::variance($this->datay));
$this->assertEquals(526.0824, round(Stats::variance($this->dataz), 4));
}