BayesServer Namespace 
Class  Description  

ArcReversal 
Contains methods to reverse the direction of a Link, known as arc reversal.
 
Cancellation 
Class for canceling long running operations.
 
CLGaussian 
Represents a Conditional Linear Gaussian probability distribution.
 
CustomProperty 
Stores a custom property.
 
CustomPropertyCollection 
Stores custom properties for a variety of objects.
 
Dag 
Includes methods for testing whether a network is a Directed Acyclic Graph (DAG).
 
DecomposeOptions 
Options used by the Decomposer class.
 
DecomposeOutput 
Contains information returned by Decompose.
 
Decomposer 
Contains methods to decompose nodes with multiple variables into their single variable equivalents.
 
InvalidNetworkException 
Raised when a network has not been correctly specified.
 
License 
Provides license validation.
 
Link 
Represents a directed link in a Bayesian network.
 
MultipleIterator 
Provides methods to iterate over multiple distributions.
 
Network 
Represents a Bayesian Network, or a Dynamic Bayesian Network. To perform inference with a network see the BayesServer.Inference namespace.
 
NetworkLinkCollection  
NetworkNodeCollection  
NetworkNodeGroupCollection 
A collection of groups.
 
NetworkVariableCollection 
Represents a readonly collection of variables that belong to a network. When a variable is added to a Node it is automatically inserted into this collection.
 
Node 
Represents a node with one or more variables in a Bayesian network.
 
NodeDistributionChangedEventArgs 
Contains information passed by DistributionChanged.
 
NodeDistributionOptions 
Options that apply to all distributions of a particular node.
 
NodeDistributions 
Represents the distributions assigned to a Node. Temporal nodes may require more than one distribution to be fully specified.
 
NodeGroup 
Allows nodes to be assigned to one or more groups.
 
NodeGroupCollection 
Represents the collection of groups a node belongs to.
 
NodeLinkCollection 
Represents a readonly collection of links. To add a link to a network see Links.
 
NodeVariableCollection 
Represents the collection of variables belonging to a .
 
NotInDomainException 
Raised when the arguments to a mathematic function are not in the domain of the function (undefined).
 
NotSpdException 
Raised when a matrix is not positive definite.
 
ParameterCounter 
Contains methods to determine the number of parameters in a Bayesian network or distribution.
 
ParameterCountOptions 
Options for ParameterCounter.
 
State 
Represents a state of a variable. E.g. the discrete variable Gender might have two states, Male and Female.
 
StateCollection 
Represents a collection of states belonging to a Variable.
 
Table 
Used to represent conditional probability distributions, joint probability distributions and more general potentials, over a number of discrete variables.
 
TableAccessor 
Allows random access to the values in a Table, using a preferred variable ordering, as opposed to the default sorted order specified in SortedVariables.
 
TableIterator 
Allows sequential access to the values in a Table, using a preferred variable ordering, as opposed to the default sorted order specified in SortedVariables.
 
TopologicalSort 
Contains methods to sort nodes in a Bayesian network in topological order.
 
Unroller 
Unrolls a Dynamic Bayesian network into the equivalent Bayesian network.
 
UnrollOptions 
Options governing the unrolling of a Dynamic Bayesian network.
 
UnrollOutput 
Contains information returned by Unroll.
 
Variable 
Represents a discrete or continuous random variable.
 
VariableContext 
Represents a variable and associated information such as time, and whether it is marked as head or tail.
 
VariableContextCollection 
Represents a readonly collection of variables.
 
VariableMap 
Maps between a custom variable order and the default sorted variable order.

Structure  Description  

Bounds 
Stores the position and size of an element.
 
IntervalT 
An interval, defined by a minimum and maximum with respective open or closed endpoints.
 
NodeDistributionKey 
Identifies a distribution assigned or to be assigned to a node.
 
StateContext 
Identifies a State and contextual information such as the time (zero based).
 
TableMarginalizeLowMemoryOptions 
Options controlling MarginalizeLowMemory.
 
ValidationOptions 
Represents options that govern the validation of a network. See Validate.

Interface  Description  

ICancellation 
Interface for cancelling long running operations.
 
IDistribution 
Interface specifying the required methods and properties for a probability distribution. For example the Table class implements this interface.
 
IStop 
Interface to allow early completion of a long running task.

Delegate  Description  

MultipleIteratorCombination 
Called by the Iterate methods to indicate a new iteration / combination.

Enumeration  Description  

HeadTail 
Indicates whether a variable is marked as head or tail in a distribution. See VariableContext.
 
IntervalEndPoint 
The type of end point for an interval.
 
NodeDistributionKind 
The kind of distribution, such as a standard Probability or Experience table.
 
NoisyOrder 
Determines the order in which the states of a parent of a noisy node increasingly affect the noisy states.
 
NoisyType 
Identifies the noisy node type, if any.
 
PropagationMethod 
The propagation method used during inference.
 
StateValueType 
The type of value represented by a State.
 
TemporalType 
The node type for networks that include temporal/sequential support. I.e. Dynamic Bayesian Networks (DBN).
 
VariableKind 
The kind of variable, such as Probability, Decision or Utility.
 
VariableValueType 
The type of data represented by a Variable.
