Example2: Linear Regression

import com.imsl.stat.*;
import com.imsl.math.*;

public class LinearRegressionEx2 {
    public static void main(String args[]) {
        // 
        LinearRegression r = new LinearRegression(2, true);
        double y[] = {3, 4, 5, 7, 7, 8, 9};
        double x[][] = {{1, 1},{1, 2},{1, 3},{1,4},{1,5},{0,6},{1,7}};
        double [][] results = new double[7][5];
        double [] confint = new double[2];
        r.update(x, y);
        for (int k=0; k<7; k++){
           LinearRegression.CaseStatistics cs = r.getCaseStatistics(x[k],y[k]);
           results[k][0] = cs.getJackknifeResidual();
           results[k][1] = cs.getCooksDistance();
           results[k][2] = cs.getDFFITS();
           confint = cs.getConfidenceInterval();
           results[k][3] = confint[0];
           results[k][4] = confint[1];
        }
        PrintMatrix p = new PrintMatrix("Selected Case Statistics");
        PrintMatrixFormat mf = new PrintMatrixFormat();
        String labels[] = {
            "Jackknife Residual.","Cook's D","DFFITS", 
            "[Conf. Interval", "on the Mean]"};
        mf.setColumnLabels(labels);
        p.print(mf, results);
    }
}

Output

                        Selected Case Statistics
   Jackknife Residual.  Cook's D  DFFITS  [Conf. Interval  on the Mean]  
0           ?             3.201     ?          1.047          2.782      
1           ?             3.92      ?          1.239          2.59       
2           ?             4.292     ?          1.37           2.459      
3           ?            10.393     ?          1.391          2.437      
4           ?            17.632     ?          1.292          2.537      
5           ?             ?         ?          0.651          3.178      
6           ?           407.199     ?          0.901          2.927