public function regress(array $dependentData, array $independentData)
{
$design = new Matrix($independentData);
$observed = (new Matrix([$dependentData]))->transpose();
if ($design->columns >= $design->rows) {
throw new InvalidArgumentException('Not enough observations to perform regression. You need to have more observations than explanatory variables.');
}
$designTranspose = $design->transpose();
$prediction = $designTranspose->multiply($design)->inverse()->multiply($designTranspose->multiply($observed));
// Extract the vertical vector as a simple array.
return $prediction->transpose()->toArray()[0];
}
/**
* @param self $other
* @return self
* @throws MatrixException
*/
public function concatenateRight(self $other) : self
{
return $this->spliceColumns($this->getColumnCount(), 0, $other->toArray());
}
/**
* @param Matrix $matrix
* @return boolean
*/
public function equals(Matrix $matrix) : bool
{
return $this->toArray() === $matrix->toArray();
}
/**
* @return Matrix
*/
public function upper() : Matrix
{
return $this->decomposition->upper(false);
}
public function testGetLower()
{
$matrix = new Matrix([[2, 0, 2, 0.6], [3, 3, 4, -2], [5, 5, 4, 2], [-1, -2, 3.4, -1]]);
$lower = $matrix->lower(true);
static::assertEquals(1, $lower->get(0, 0));
static::assertEquals(0, $lower->get(0, 1));
static::assertEquals(0, $lower->get(0, 2));
static::assertEquals(0, $lower->get(0, 3));
static::assertEquals(3, $lower->get(1, 0));
static::assertEquals(1, $lower->get(1, 1));
static::assertEquals(0, $lower->get(1, 2));
static::assertEquals(0, $lower->get(1, 3));
static::assertEquals(5, $lower->get(2, 0));
static::assertEquals(5, $lower->get(2, 1));
static::assertEquals(1, $lower->get(2, 2));
static::assertEquals(0, $lower->get(2, 3));
static::assertEquals(-1, $lower->get(3, 0));
static::assertEquals(-2, $lower->get(3, 1));
static::assertEquals(3.4, $lower->get(3, 2));
static::assertEquals(1, $lower->get(3, 3));
}
/**
* @param Observations $observations
* @return array
* @throws InvalidArgumentException
*/
public function regress(Observations $observations) : array
{
$design = new Matrix($observations->getFeatures());
$observed = (new Matrix([$observations->getOutcomes()]))->transpose();
if ($design->getRowCount() < $design->getColumnCount()) {
throw new InvalidArgumentException('Not enough observations to perform regression. You need to have more observations than explanatory variables.');
}
$designTranspose = $design->transpose();
$prediction = $designTranspose->multiplyMatrix($design)->inverse()->multiplyMatrix($designTranspose->multiplyMatrix($observed));
return $prediction->transpose()->toArray()[0];
}
