wls-java

weighted linear regression in pure Java w/o any 3d party dependency or framework.

the idea is similar to statsmodels.regression.linear_model.WLS.fit

General Info

WLS is based on the OLS method and help solve problems of model inadequacy or violations of the basic regression assumptions.

Estimating a linear regression with WLS is useful, but can be appear to be daunting w/o special stats packages, e.g. python statsmodels, spark & the like.

How-to

import org.vspaz.wls.*;

public class Main {
    public static void main(String [] args) {
        double[] xPoints = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0};
        double[] yPoints = {1.0, 3.0, 4.0, 5.0, 2.0, 3.0, 4.0};
        double[] weights = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0};

        Wls wlsModel = new Wls(xPoints, yPoints, weights);
        Point point = wlsModel.fitLinearRegression();

        System.out.println(point.getIntercept());
        System.out.println(point.getSlope());
    }
}

Run the example

 mvn clean compile assembly:single
 java -jar wls.jar

References

• Wikipedia: Weighted least squares
• Introduction to Linear Regression Analysis, 5th edition
• Least Squares Regression Analysis in Terms of Linear Algebra