public CategoricalDistribution posteriorDistribution(IProposition phi,
params IProposition[] evidence)
{
IProposition conjEvidence = ProbUtil.constructConjunction(evidence);
// P(A | B) = P(A AND B)/P(B) - (13.3 AIMA3e)
CategoricalDistribution dAandB = jointDistribution(phi, conjEvidence);
CategoricalDistribution dEvidence = jointDistribution(conjEvidence);
return(dAandB.divideBy(dEvidence));
}
public CategoricalDistributionIteratorAdapter(
CategoricalDistribution.Iterator cdi)
{
this.cdi = cdi;
}
public void iterateOver(CategoricalDistribution.Iterator cdi,
params AssignmentProposition[] fixedValues)
{
iterateOverTable(new CategoricalDistributionIteratorAdapter(cdi),
fixedValues);
}
public override void iterateOver(CategoricalDistribution.Iterator cdi)
{
iterateOverTable(new CategoricalDistributionIteratorAdapter(cdi));
}
public override CategoricalDistribution multiplyByPOS(
CategoricalDistribution multiplier, params RandomVariable[] prodVarOrder)
{
return pointwiseProductPOS((ProbabilityTable) multiplier, prodVarOrder);
}
public override CategoricalDistribution multiplyBy(CategoricalDistribution multiplier)
{
return pointwiseProduct((ProbabilityTable) multiplier);
}
public override CategoricalDistribution divideBy(CategoricalDistribution divisor)
{
return divideBy((ProbabilityTable) divisor);
}
/**
* Multiplication - Product Order Specified (POS). <b>Note:</b> Is
* equivalent to pointwise product calculation.<br>
* <br>
* see: AIMA3e Figure 14.10 page 527.<br>
* <br>
* Multiplication of this Distribution by a given multiplier, creating a new
* Distribution representing the product of the two. The order of the
* variables comprising the product will match those specified. For example
* (the General case of Baye's rule, AIMA3e pg. 496), using this API method:<br>
* <br>
* <b>P</b>(Y | X) = (<b>P</b>(X | Y)<b>P</b>(Y), [Y, X])/<b>P</b>(X)<br>
* <br>
* is true when the correct product order is specified.
*
* @param multiplier
* @param prodVarOrder
* the order the variables comprising the product are to be in.
*
* @return a new Distribution representing the product of this and the
* passed in multiplier. The order of the variables comprising the
* product distribution is the order specified.
*
* @see CategoricalDistribution#multiplyBy(CategoricalDistribution)
*/
public abstract CategoricalDistribution multiplyByPOS(CategoricalDistribution multiplier,
params RandomVariable[] prodVarOrder);
/** * Multiplication of this Distribution by a given multiplier, creating a new * Distribution representing the product of the two. <b>Note:</b> Is * equivalent to pointwise product calculation on factors.<br> * <br> * see: AIMA3e Figure 14.10 page 527.<br> * <br> * Note: Default Distribution multiplication is not commutative. The reason * is because the order of the variables comprising a Distribution dictate * the ordering of the values for that distribution. For example (the * General case of Baye's rule, AIMA3e pg. 496), using this API method:<br> * <br> * <b>P</b>(Y | X) = (<b>P</b>(X | Y)<b>P</b>(Y))/<b>P</b>(X)<br> * <br> * is NOT true, due to multiplication of distributions not being * commutative. However:<br> * <br> * <b>P</b>(Y | X) = (<b>P</b>(Y)<b>P</b>(X | Y))/<b>P</b>(X)<br> * <br> * is true, using this API.<br> * <br> * The default order of the variable of the Distribution returned is the * order of the variables as they are seen, as read from the left to right * term, for e.g.: <br> * <br> * <b>P</b>(Y)<b>P</b>(X | Y)<br> * <br> * would give a Distribution of the following form: <br> * Y, X<br> * <br> * i.e. an ordered union of the variables from the two distributions. <br> * To override the default order of the product use multiplyByPOS(). * * @param multiplier * * @return a new Distribution representing the product of this and the * passed in multiplier. The order of the variables comprising the * product distribution is the ordered union of the left term (this) * and the right term (multiplier). * * @see CategoricalDistribution#multiplyByPOS(CategoricalDistribution, * params RandomVariable []) */ public abstract CategoricalDistribution multiplyBy(CategoricalDistribution multiplier);
/** * Divide the dividend (this) CategoricalDistribution by the divisor to * create a new CategoricalDistribution representing the quotient. The * variables comprising the divisor distribution must be a subset of the * dividend. However, ordering of variables does not matter as the quotient * contains the same variables as the dividend and the internal * implementation logic should handle iterating through the two * distributions correctly, irrespective of the order of their variables. * * @param divisor * @return a new Distribution representing the quotient of the dividend * (this) divided by the divisor. * @throws IllegalArgumentException * if the variables of the divisor distribution are not a subset * of the dividend. */ public abstract CategoricalDistribution divideBy(CategoricalDistribution divisor);
/**
* Multiplication - Product Order Specified (POS). <b>Note:</b> Is
* equivalent to pointwise product calculation.<br>
* <br>
* see: AIMA3e Figure 14.10 page 527.<br>
* <br>
* Multiplication of this Distribution by a given multiplier, creating a new
* Distribution representing the product of the two. The order of the
* variables comprising the product will match those specified. For example
* (the General case of Baye's rule, AIMA3e pg. 496), using this API method:<br>
* <br>
* <b>P</b>(Y | X) = (<b>P</b>(X | Y)<b>P</b>(Y), [Y, X])/<b>P</b>(X)<br>
* <br>
* is true when the correct product order is specified.
*
* @param multiplier
* @param prodVarOrder
* the order the variables comprising the product are to be in.
*
* @return a new Distribution representing the product of this and the
* passed in multiplier. The order of the variables comprising the
* product distribution is the order specified.
*
* @see CategoricalDistribution#multiplyBy(CategoricalDistribution)
*/
public abstract CategoricalDistribution multiplyByPOS(CategoricalDistribution multiplier,
params RandomVariable[] prodVarOrder);
/** * Multiplication of this Distribution by a given multiplier, creating a new * Distribution representing the product of the two. <b>Note:</b> Is * equivalent to pointwise product calculation on factors.<br> * <br> * see: AIMA3e Figure 14.10 page 527.<br> * <br> * Note: Default Distribution multiplication is not commutative. The reason * is because the order of the variables comprising a Distribution dictate * the ordering of the values for that distribution. For example (the * General case of Baye's rule, AIMA3e pg. 496), using this API method:<br> * <br> * <b>P</b>(Y | X) = (<b>P</b>(X | Y)<b>P</b>(Y))/<b>P</b>(X)<br> * <br> * is NOT true, due to multiplication of distributions not being * commutative. However:<br> * <br> * <b>P</b>(Y | X) = (<b>P</b>(Y)<b>P</b>(X | Y))/<b>P</b>(X)<br> * <br> * is true, using this API.<br> * <br> * The default order of the variable of the Distribution returned is the * order of the variables as they are seen, as read from the left to right * term, for e.g.: <br> * <br> * <b>P</b>(Y)<b>P</b>(X | Y)<br> * <br> * would give a Distribution of the following form: <br> * Y, X<br> * <br> * i.e. an ordered union of the variables from the two distributions. <br> * To override the default order of the product use multiplyByPOS(). * * @param multiplier * * @return a new Distribution representing the product of this and the * passed in multiplier. The order of the variables comprising the * product distribution is the ordered union of the left term (this) * and the right term (multiplier). * * @see CategoricalDistribution#multiplyByPOS(CategoricalDistribution, * params RandomVariable []) */ public abstract CategoricalDistribution multiplyBy(CategoricalDistribution multiplier);
/** * Divide the dividend (this) CategoricalDistribution by the divisor to * create a new CategoricalDistribution representing the quotient. The * variables comprising the divisor distribution must be a subset of the * dividend. However, ordering of variables does not matter as the quotient * contains the same variables as the dividend and the internal * implementation logic should handle iterating through the two * distributions correctly, irrespective of the order of their variables. * * @param divisor * @return a new Distribution representing the quotient of the dividend * (this) divided by the divisor. * @throws IllegalArgumentException * if the variables of the divisor distribution are not a subset * of the dividend. */ public abstract CategoricalDistribution divideBy(CategoricalDistribution divisor);