MCordingley\Regression\StatisticsGatherer\Linear::getStandardErrorCoefficients PHP Метод

    public function getStandardErrorCoefficients() : array
    {
        if (is_null($this->SCoefficients)) {
            $design = new Matrix($this->observations->getFeatures());
            $inverted = $design->transpose()->multiplyMatrix($design)->inverse();
            $diagonalVector = [];
            for ($i = 0, $size = $inverted->getRowCount(); $i < $size; $i++) {
                $diagonalVector[] = $inverted->get($i, $i);
            }
            $this->SCoefficients = (new Matrix([$diagonalVector]))->multiplyScalar($this->getMeanSquaredError())->map(function ($element) {
                return sqrt($element);
            })->toArray()[0];
        }
        return $this->SCoefficients;
    }

 public function testStatistics()
 {
     $observations = Observations::fromArray($this->getFeatures(), $this->getOutcomes());
     $coefficients = [1.0954970633022, 0.92451598868827];
     $predictor = new LinearPredictor($coefficients);
     $statisticsGatherer = new LinearStatisticsGatherer($observations, $coefficients, $predictor);
     static::assertEquals(4, $statisticsGatherer->getDegreesOfFreedomTotal());
     static::assertEquals(3, $statisticsGatherer->getDegreesOfFreedomError());
     static::assertEquals(1, $statisticsGatherer->getDegreesOfFreedomModel());
     static::assertEquals(1.94, round($statisticsGatherer->getFStatistic(), 2));
     static::assertEquals(0.39, round($statisticsGatherer->getRSquared(), 2));
     $stdErrorCoefficients = $statisticsGatherer->getStandardErrorCoefficients();
     static::assertEquals(1.51, round($stdErrorCoefficients[0], 2));
     static::assertEquals(0.66, round($stdErrorCoefficients[1], 2));
     static::assertEquals(1.42, round($statisticsGatherer->getStandardError(), 2));
     $tStatistics = $statisticsGatherer->getTStatistics();
     static::assertEquals(0.73, round($tStatistics[0], 2));
     static::assertEquals(1.39, round($tStatistics[1], 2));
 }