Contains methods to reverse the direction of a Link, known as arc reversal.
Class for canceling long running operations.
Represents a Conditional Linear Gaussian probability distribution.
Stores a custom property.
Stores custom properties for a variety of objects.
Includes methods for testing whether a network is a Directed Acyclic Graph (DAG).
Options used by the Decomposer class.
Contains information returned by.
Contains methods to decompose nodes with multiple variables into their single variable equivalents.
Raised when a network has not been correctly specified.
Provides license validation.
Represents a directed link in a Bayesian network.
Provides methods to iterate over multiple distributions.
Represents a Bayesian Network, or a Dynamic Bayesian Network. To perform inference with a network see the BayesServer.Inference namespace.
A collection of groups.
Represents a read-only collection of variables that belong to a network. When a variable is added to a Node it is automatically inserted into this collection.
Represents a node with one or more variables in a Bayesian network.
Contains information passed by DistributionChanged.
Options that apply to all distributions of a particular node.
Represents the distributions assigned to a Node. Temporal nodes may require more than one distribution to be fully specified.
Allows nodes to be assigned to one or more groups.
Represents the collection of groups a node belongs to.
Represents a read-only collection of links. To add a link to a network see Links.
Represents the collection of variables belonging to a .
Raised when the arguments to a mathematic function are not in the domain of the function (undefined).
Raised when a matrix is not positive definite.
Contains methods to determine the number of parameters in a Bayesian network or distribution.
Options for ParameterCounter.
Represents a state of a variable. E.g. the discrete variable Gender might have two states, Male and Female.
Represents a collection of states belonging to a Variable.
Used to represent conditional probability distributions, joint probability distributions and more general potentials, over a number of discrete variables.
Contains methods to sort nodes in a Bayesian network in topological order.
Unrolls a Dynamic Bayesian network into the equivalent Bayesian network.
Options governing the unrolling of a Dynamic Bayesian network.
Contains information returned by.
Represents a discrete or continuous random variable.
Represents a variable and associated information such as time, and whether it is marked as head or tail.
Represents a read-only collection of variables.
Maps between a custom variable order and the default sorted variable order.
Stores the position and size of an element.
An interval, defined by a minimum and maximum with respective open or closed endpoints.
Identifies a distribution assigned or to be assigned to a node.
Identifies a State and contextual information such as the time (zero based).
Represents options that govern the validation of a network. See.
Interface for cancelling long running operations.
Interface specifying the required methods and properties for a probability distribution. For example the Table class implements this interface.
Interface to allow early completion of a long running task.
Called by the Iterate methods to indicate a new iteration / combination.
Indicates whether a variable is marked as head or tail in a distribution. See VariableContext.
The type of end point for an interval.
The kind of distribution, such as a standard Probability or Experience table.
Determines the order in which the states of a parent of a noisy node increasingly affect the noisy states.
Identifies the noisy node type, if any.
The propagation method used during inference.
The type of value represented by a State.
The node type for networks that include temporal/sequential support. I.e. Dynamic Bayesian Networks (DBN).
The kind of variable, such as Probability, Decision or Utility.
The type of data represented by a Variable.