import org.apache.commons.math.linear.MatrixUtils;
import org.apache.commons.math.linear.RealMatrix;

public class PageRanker {

  ...

  public double[] solve() {
    int len = pages.length;
    double[][] a = new double[len][len];
    for (int j = 0; j < len; j++) {
      int n = 0;
      for (int i = 0; i < len; i++) {
        n += links[i][j];
      }
      double v = -1. * dampingFactor / (double)(n==0?(len-1):n);
      for (int i = 0; i < len; i++) {
        a[i][j] = (i==j)?1.:((double)(n==0?1:links[i][j])*v);
      }
    }
    if (dampingFactor == 1.) {
      for (int j = 0; j < len; j++) {
        a[0][j] = 1.;
      }
    }
    RealMatrix A = MatrixUtils.createRealMatrix(a);

    double[] b = new double[len];
    if (dampingFactor == 1.) {
      b[0] = 1.;
      for (int i = 1; i < len; i++) {
        b[i] = 0.;
      }
    }
    else {
      double v = (1. - dampingFactor) / (double)len;
      for (int i = 0; i < len; i++) {
        b[i] = v;
      }
    }
    RealMatrix B = MatrixUtils.createRowRealMatrix(b).transpose();

    RealMatrix X = A.solve(B);

    double[] pageRanks = new double[len];
    for (int i = 0; i < len; i++) {
      pageRanks[i] = X.getEntry(i, 0);
    }
    return pageRanks;
  }
} 

$ javac -classpath commons-math-1.2.jar PageRanker.java
$ java -classpath .:commons-math-1.2.jar PageRankExample1
A       0.0303
B       0.3854
C       0.3438
D       0.0392
E       0.0811
F       0.0392
g       0.0162
h       0.0162
i       0.0162
j       0.0162
k       0.0162
$ java -classpath .:commons-math-1.2.jar PageRankExample2
ID=1    0.3035
ID=2    0.1661
ID=3    0.1406
ID=4    0.1054
ID=5    0.1789
ID=6    0.0447
ID=7    0.0607
$