/**
* __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
* @param BasicStats $stats instance of basic stats
* @return LinearRegression An object representing the regression model
*/
public function __construct(array $datax, array $datay, BasicStats $stats)
{
$this->beta = $stats->covariance($datax, $datay) / $stats->variance($datax);
$this->alpha = $stats->average($datay) - $this->beta * $stats->average($datax);
$this->r = $stats->correlation($datax, $datay);
parent::__construct($datax, $datay, $stats);
}
/**
* __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
* @param BasicStats $stats instance of basic stats
* @return LogarithmicRegression An object representing the regression model
*/
public function __construct($datax, $datay, BasicStats $stats)
{
$logx = array();
foreach ($datax as $x) {
$logx[] = log($x);
}
$this->r = $stats->correlation($logx, $datay);
$this->beta = $stats->covariance($logx, $datay) / $stats->variance($logx);
$this->alpha = $stats->average($datay) - $this->beta * $stats->average($logx);
parent::__construct($datax, $datay, $stats);
}
/**
* __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
* @param BasicStats $stats instance of basic stats
* @return ExponentialRegression An object representing the regression model
*/
public function __construct(array $datax, array $datay, BasicStats $stats)
{
$logy = array();
foreach ($datay as $y) {
$logy[] = log($y);
}
$this->r = $stats->correlation($datax, $logy);
$logbeta = $stats->covariance($datax, $logy) / $stats->variance($datax);
$logalpha = $stats->average($logy) - $logbeta * $stats->average($datax);
$this->beta = exp($logbeta);
$this->alpha = exp($logalpha);
parent::__construct($datax, $datay, $stats);
}
/**
* Dot Multiply function
*
* Multiplies this matrix against a second matrix
*
* @param matrix $matrixA The first matrix in the multiplication
* @param matrix $matrixB The second matrix in the multiplication
* @return matrix The multiplied matrix
*/
public function dotMultiply(Matrix $matrixA, Matrix $matrixB)
{
$this->util->multiplyCheck($matrixA, $matrixB);
$rows = $matrixA->getRows();
$columns = $matrixB->getColumns();
$newMatrix = $this->builder->zero($rows, $columns);
for ($i = 1; $i <= $rows; $i++) {
for ($j = 1; $j <= $columns; $j++) {
$row = $matrixA->getRow($i);
$column = array();
for ($k = 1; $k <= $rows; $k++) {
$column[] = $matrixB->getElement($k, $j);
}
$newMatrix->setElement($i, $j, $this->basic->sumXY($row, $column));
}
}
return $newMatrix;
}
