java programming

Question

a) Write a method that takes as input a 2-dimensional matrix representing the joint probability distribution over two variables, and returns the marginal probability distribution for either the row or column variable as a 1-dimensional array. Include a Boolean parameter that allows the caller to specify whether to compute the marginals for the row or column variable. 

b) Write a method that takes as input a 2-dimensional matrix representing the joint probability distribution over two variables, and returns a Boolean value that is true if and only if the two variables are independent. 

Answer 1

class Probability

{

public static final double EPSILON = 0.0000001; //sets the precision: currently 6 digits

//TRUE --> rows; FALSE--> Columns;

public void marginalProbabilityDistribution( double A[][], double k[], boolean rowColumnFlag )

{

if (rowColumnFlag)

{

int N = A.length;

System.out.println(" row totals ");

for (int iLoop=0; iLoop<N; iLoop++)

{

double rowSum=0;

for (int jLoop=0; jLoop<A[iLoop].length; jLoop++)

{

rowSum += A[iLoop][jLoop];

}

k[iLoop]=rowSum;

System.out.println( (iLoop+1) + "th row sum is " + k[iLoop]);

} //for

}

else

{

int N = A[0].length;

System.out.println(" column totals ");

for (int iLoop=0; iLoop<N; iLoop++)

{

double columnSum = 0;

for (int jLoop=0; jLoop<A.length; jLoop++)

{

columnSum += A[jLoop][iLoop];

}

k[iLoop]=columnSum;

System.out.println( (iLoop+1) + "th column sum is " + k[iLoop]);

} //for

} //main if

} //method

public boolean IsIndependant( double A[][])

{

boolean boolReturn = true;

int numRows = A.length;

int numCols = A[0].length;

double xMarginal[] = new double[numRows];

double yMarginal[] = new double[numCols];

marginalProbabilityDistribution(A,xMarginal,true);

marginalProbabilityDistribution(A,yMarginal,false);

for (int iLoop=0; iLoop<numRows; iLoop++)

{

for (int jLoop=0; jLoop<numCols; jLoop++)

{

if ((A[iLoop][jLoop]-xMarginal[iLoop]*yMarginal[jLoop])> this.EPSILON)

{

boolReturn=false;

break;

}

}

}

return(boolReturn);

}

public static void main(String args[])

{

double A[][] = new double[6][6];

for (int iLoop=0; iLoop<6; iLoop++)

{

for (int jLoop=0; jLoop<6; jLoop++)

{

A[iLoop][jLoop] = (double) (1.0000000f/36);

}

}

double k[] = new double[6];

Probability P = new Probability();

P.marginalProbabilityDistribution(A,k,false);

for (int iLoop=0; iLoop<6; iLoop++)

{

System.out.println(k[iLoop]);

}

System.out.println(P.IsIndependant(A));

}

}