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- <?php
- namespace MathPHP\Statistics\Regression;
- use MathPHP\Exception;
- /**
- * Simple linear regression - least squares method
- *
- * A model with a single explanatory variable.
- * Fits a straight line through the set of n points in such a way that makes
- * the sum of squared residuals of the model (that is, vertical distances
- * between the points of the data set and the fitted line) as small as possible.
- * https://en.wikipedia.org/wiki/Simple_linear_regression
- *
- * Having data points {(xᵢ, yᵢ), i = 1 ..., n }
- * Find the equation y = mx + b
- *
- * _ _ __
- * x y - xy
- * m = _________
- * _ __
- * (x)² - x²
- *
- * _ _
- * b = y - mx
- */
- class Linear extends ParametricRegression
- {
- use Methods\LeastSquares;
- use Models\LinearModel;
- /**
- * Calculates the regression parameters.
- *
- * @throws Exception\BadDataException
- * @throws Exception\IncorrectTypeException
- * @throws Exception\MatrixException
- * @throws Exception\MathException
- */
- public function calculate(): void
- {
- $this->parameters = $this->leastSquares($this->ys, $this->xs)->getColumn(0);
- }
- /**
- * Evaluate the regression equation at x
- * Uses the instance model's evaluateModel method.
- *
- * @param float $x
- *
- * @return float
- */
- public function evaluate(float $x): float
- {
- return $this->evaluateModel($x, $this->parameters);
- }
- }
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