Method Detail

• calculateMutualInformation

  public static double calculateMutualInformation(double[] firstVector,
                                                  double[] secondVector)

  Calculates the Mutual Information I(X;Y) between two random variables. Uses histograms to estimate the probability distributions, and thus the information. The mutual information is bounded 0 ≤ I(X;Y) ≤ min(H(X),H(Y)). It is also symmetric, so I(X;Y) = I(Y;X).

  Parameters:

  firstVector - Input vector (X). It is discretised to the floor of each value before calculation.

  secondVector - Input vector (Y). It is discretised to the floor of each value before calculation.

  Returns:

  The Mutual Information I(X;Y).

• calculateConditionalMutualInformation

  public static double calculateConditionalMutualInformation(double[] firstVector,
                                                             double[] secondVector,
                                                             double[] conditionVector)

  Calculates the conditional Mutual Information I(X;Y|Z) between two random variables, conditioned on a third. Uses histograms to estimate the probability distributions, and thus the information. The conditional mutual information is bounded 0 ≤ I(X;Y) ≤ min(H(X|Z),H(Y|Z)). It is also symmetric, so I(X;Y|Z) = I(Y;X|Z).

  Parameters:

  firstVector - Input vector (X). It is discretised to the floor of each value before calculation.

  secondVector - Input vector (Y). It is discretised to the floor of each value before calculation.

  conditionVector - Input vector (Z). It is discretised to the floor of each value before calculation.

  Returns:

  The conditional Mutual Information I(X;Y|Z).