LinearRegression.java

import org.apache.commons.math3.stat.regression.OLSMultipleLinearRegression;
public class LinearRegression {
    public static void main(String[] args) {
        double [] y =  {-0.48812477,  0.33458213,  
                        -0.52754476, -0.79863471,
                        -0.68544309, -0.12970239,
                         0.02355622, -0.31890850,
                         0.34725819,  0.08108851};
        double [][] x = {{1,0}, {0,0},
                         {1,0}, {2,1},
                         {0,1}, {0,0},
                         {1,0}, {0,0},
                         {1,0}, {0,0}};
        double [][] xb = {{1,0,0}, {0,0,0},
                          {1,0,0}, {2,1,2},
                          {0,1,0}, {0,0,0},
                          {1,0,0}, {0,0,0},
                          {1,0,0}, {0,0,0}};
        
        OLSMultipleLinearRegression regression = new OLSMultipleLinearRegression();
        regression.newSampleData(y, x);
        double[] beta = regression.estimateRegressionParameters();   
        
        System.out.printf("First model: y = int + genoA + genoB\n");
        System.out.printf("Intercept: %.3f\t", beta[0]);
        System.out.printf("beta1: %.3f\t", beta[1]);
        System.out.printf("beta2: %.3f\n\n", beta[2]);

        regression.newSampleData(y, xb);
        double[] betab = regression.estimateRegressionParameters();   
        
        System.out.printf("Second model: y = int + genoA + genoB + genoA:genoB\n");
        System.out.printf("Intercept: %.3f\t", betab[0]);
        System.out.printf("beta1: %.3f\t", betab[1]);
        System.out.printf("beta2: %.3f\t", betab[2]);
        System.out.printf("beta2: %.3f\n", betab[3]);
    }
}