Overview | Package | Class | Use | Tree | Deprecated | Index | Help
PREV NEXT | FRAMES NO FRAMES

## Uses of Package
de.jstacs.models.discrete.inhomogeneous

Packages that use de.jstacs.models.discrete.inhomogeneous
de.jstacs.models | Provides the interface `Model` and its abstract implementation `AbstractModel`, which is the super class of all other models.
de.jstacs.models.discrete |
de.jstacs.models.discrete.inhomogeneous | This package contains various inhomogeneous models.
de.jstacs.models.discrete.inhomogeneous.parameters |
de.jstacs.models.discrete.inhomogeneous.shared |

Classes in de.jstacs.models.discrete.inhomogeneous used by de.jstacs.models
BayesianNetworkModel The class implements a Bayesian network ( `StructureLearner.ModelType.BN` ) of fixed order.
FSDAGModel This class can be used for any discrete fixed structure directed acyclic graphical model ( `FSDAGModel`).

Classes in de.jstacs.models.discrete.inhomogeneous used by de.jstacs.models.discrete
InhCondProb This class handles (conditional) probabilities of sequences for inhomogeneous models.
MEMConstraint This constraint can be used for any maximum entropy model (MEM) application.

Classes in de.jstacs.models.discrete.inhomogeneous used by de.jstacs.models.discrete.inhomogeneous
BayesianNetworkModel The class implements a Bayesian network ( `StructureLearner.ModelType.BN` ) of fixed order.
DAGModel The abstract class for directed acyclic graphical models (`DAGModel`).
FSDAGModel This class can be used for any discrete fixed structure directed acyclic graphical model ( `FSDAGModel`).
FSDAGModelForGibbsSampling This is the class for a fixed structure directed acyclic graphical model (see `FSDAGModel`) that can be used in a Gibbs sampling.
InhCondProb This class handles (conditional) probabilities of sequences for inhomogeneous models.
InhConstraint This class is the superclass for all inhomogeneous constraints.
InhomogeneousDGM This class is the main class for all inhomogeneous discrete graphical models (`InhomogeneousDGM`).
MEMConstraint This constraint can be used for any maximum entropy model (MEM) application.
SequenceIterator This class is used to iterate over a discrete sequence.
StructureLearner.LearningType This `enum` defines the different types of learning that are possible with the `StructureLearner`.
StructureLearner.ModelType This `enum` defines the different types of models that can be learned with the `StructureLearner`.

Classes in de.jstacs.models.discrete.inhomogeneous used by de.jstacs.models.discrete.inhomogeneous.parameters
FSDAGModel This class can be used for any discrete fixed structure directed acyclic graphical model ( `FSDAGModel`).
InhomogeneousDGM This class is the main class for all inhomogeneous discrete graphical models (`InhomogeneousDGM`).
StructureLearner.LearningType This `enum` defines the different types of learning that are possible with the `StructureLearner`.
StructureLearner.ModelType This `enum` defines the different types of models that can be learned with the `StructureLearner`.

Classes in de.jstacs.models.discrete.inhomogeneous used by de.jstacs.models.discrete.inhomogeneous.shared
FSDAGModel This class can be used for any discrete fixed structure directed acyclic graphical model ( `FSDAGModel`).
StructureLearner.LearningType This `enum` defines the different types of learning that are possible with the `StructureLearner`.
StructureLearner.ModelType This `enum` defines the different types of models that can be learned with the `StructureLearner`.

Overview | Package | Class | Use | Tree | Deprecated | Index | Help
PREV NEXT | FRAMES NO FRAMES