Uses of Enum Class
edu.pitt.dbmi.algo.bayesian.constraint.inference.BCInference.OP

Packages that use BCInference.OP

Package	Description
edu.cmu.tetrad.search.test	Contains classes for running conditional independence tests for various sorts of data.
edu.cmu.tetrad.search.work_in_progress	Contains some classes that aren't ready for prime time.
edu.pitt.dbmi.algo.bayesian.constraint.inference

Uses of BCInference.OP in edu.cmu.tetrad.search.test

Methods in edu.cmu.tetrad.search.test with parameters of type BCInference.OP

Modifier and Type	Method	Description
double	IndTestProbabilistic.probConstraint(BCInference bci, BCInference.OP op, Node x, Node y, Node[] z, Map<Node,Integer> indices)	Returns the probability of the constraint x op y | z.

Uses of BCInference.OP in edu.cmu.tetrad.search.work_in_progress

Methods in edu.cmu.tetrad.search.work_in_progress with parameters of type BCInference.OP

Modifier and Type	Method	Description
double	ProbabilisticMapIndependence.probConstraint(BCInference.OP op, Node x, Node y, Node[] z)	probConstraint.

Uses of BCInference.OP in edu.pitt.dbmi.algo.bayesian.constraint.inference

Methods in edu.pitt.dbmi.algo.bayesian.constraint.inference that return BCInference.OP

Modifier and Type	Method	Description
static BCInference.OP	BCInference.OP.valueOf(String name)	Returns the enum constant of this class with the specified name.
static BCInference.OP[]	BCInference.OP.values()	Returns an array containing the constants of this enum class, in the order they are declared.

Methods in edu.pitt.dbmi.algo.bayesian.constraint.inference with parameters of type BCInference.OP

Modifier and Type	Method	Description
double	BCInference.probConstraint(BCInference.OP constraint, int x, int y, int[] z)	This function takes a constraint, which has a value of either OP.dependent or OP.independent, of the form "X independent Y given Z" or "X dependent Y given Z" and returns a probability for that constraint given the data in cases and assumed prior probability for that constraint given the data in cases and assumed prior probabilities.