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
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.
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());
}
} mvn clean compile assembly:single
java -jar wls.jar
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