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GClasses
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A node in a belief network that represents a Pareto distribution.
#include <GBayesianNetwork.h>
Public Member Functions | |
| GBNPareto (GBNNode *pDefaultVal) | |
| General-purpose constructor. The prior mean and deviation parameters are for the Metropolis algorithm. pDefaultVal specifies a bogus value to be used for the parameters of this distribution. Typically, you will change these values (by calling setAlphaAndM) after constructing this node. More... | |
| virtual | ~GBNPareto () |
| virtual void | addCatParent (GBNCategorical *pNode, GBNNode *pDefaultVal) |
| Adds a categorical node as a parent of this node. Calling this method will cause This node to resize its table of distribution parameters, so a default value is required to fill in new elements. Typically, you will set these new elements to something more meaningful (by calling setAlphaAndM) after you call this method. More... | |
| virtual double | initMean () |
| See the comment for GBNMetropolisNode::initMean() More... | |
| virtual bool | isDiscrete () |
| Returns false. More... | |
| virtual double | likelihood (double x) |
| Returns the likelihood that the value x would be drawn from this distribution given the current values of all the parent nodes. More... | |
| void | setAlphaAndM (size_t cat, GBNNode *pAlpha, GBNNode *pM) |
| Set the alpha and M parameters for one of the distributions of this node. "cat" specifies the index of the combination of values (in little-endian order) in the categorical parent distributions for which this distribution is being specified. More... | |
 Public Member Functions inherited from GClasses::GBNMetropolisNode | |
| GBNMetropolisNode () | |
| General-purpose constructor. More... | |
| virtual | ~GBNMetropolisNode () |
| virtual double | currentValue () |
| Returns the most recent value sampled from this node. More... | |
| void | sample (GRand *pRand) |
| Draws a new Gibbs sample for this node given the current values of all other nodes it its Markov blanket. Uses the Metropolis algorithm to do so. More... | |
| Public Member Functions inherited from GClasses::GBNVariable | |
| GBNVariable () | |
| virtual | ~GBNVariable () |
| size_t | catCount () |
| Returns the total number of combinations of categorical values supported by the categorical parents of this node. This node is expected to specify a distribution for each of these categorical combinations. More... | |
| const std::vector< GBNVariable * > & | children () |
| Returns all nodes that are known to depend on this one. More... | |
| size_t | currentCatIndex () |
| Queries the categorical parent nodes to determine their current values, and combines them to produce a single index value that is unique for this combination of categorical values. The value this returns will be from 0 to catCount()-1. The values are organized in little-endian manner. That is, it cycles through all values supported by the first categorical parent before moving on to the next value of the next parent. More... | |
| virtual void | onNewChild (GBNVariable *pChild) |
| This method links back to the child node that just added this node as a parent. More... | |
| void | setObserved (double value) |
| Set this node to an observed value. After calling this, subsequent calls to sample will not change its value. More... | |
| void | setUnobserved () |
| Set this node to an unobserved value. After calling this, subsequent calls to sample will draw new values for this node. More... | |
| Public Member Functions inherited from GClasses::GBNNode | |
| GBNNode () | |
| virtual | ~GBNNode () |
Protected Attributes | |
| std::vector< GBNNode * > | m_alphaAndM |
| Protected Attributes inherited from GClasses::GBNMetropolisNode | |
| double | m_currentMean |
| double | m_sumOfSquaredValues |
| double | m_sumOfValues |
| Protected Attributes inherited from GClasses::GBNVariable | |
| std::vector< GBNCategorical * > | m_catParents |
| std::vector< GBNVariable * > | m_children |
| Protected Attributes inherited from GClasses::GBNNode | |
| bool | m_observed |
| double | m_observedValue |
Additional Inherited Members | |
| Protected Member Functions inherited from GClasses::GBNMetropolisNode | |
| double | markovBlanket (double x) |
| Computes the log-probability of x (as a value for this node) given the current values for the entire rest of the network (aka the complete conditional), which is equal to the log-probability of x given the Markov-Blanket of this node, which we can compute efficiently. More... | |
| void | metropolis (GRand *pRand) |
| Sample the network in a manner that can be proven to converge to a true joint distribution for the network. More... | |
| GClasses::GBNPareto::GBNPareto | ( | GBNNode * | pDefaultVal | ) |
General-purpose constructor. The prior mean and deviation parameters are for the Metropolis algorithm. pDefaultVal specifies a bogus value to be used for the parameters of this distribution. Typically, you will change these values (by calling setAlphaAndM) after constructing this node.
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inlinevirtual |
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virtual |
Adds a categorical node as a parent of this node. Calling this method will cause This node to resize its table of distribution parameters, so a default value is required to fill in new elements. Typically, you will set these new elements to something more meaningful (by calling setAlphaAndM) after you call this method.
Implements GClasses::GBNVariable.
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virtual |
See the comment for GBNMetropolisNode::initMean()
Implements GClasses::GBNMetropolisNode.
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inlinevirtual |
Returns false.
Implements GClasses::GBNMetropolisNode.
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virtual |
Returns the likelihood that the value x would be drawn from this distribution given the current values of all the parent nodes.
Implements GClasses::GBNVariable.
Set the alpha and M parameters for one of the distributions of this node. "cat" specifies the index of the combination of values (in little-endian order) in the categorical parent distributions for which this distribution is being specified.
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protected |
1.8.11