StatisticalModel (Snifflib API)

java.lang.Object
- com.mockturtlesolutions.snifflib.functions.AbstractFunction
- - com.mockturtlesolutions.snifflib.invprobs.StatisticalModel

All Implemented Interfaces:

Nameable, FigureReportable, Reportable, DeclaredParameters, DeclaredVariables, Likelihood, NamedParameters, ObjectSampler, ObjectSamplerClient, OptimizableScalar

Direct Known Subclasses:

AbstractGammaAlgorithm, AbstractIncBetaAlgorithm, AbstractLogGammaAlgorithm, AbstractProposalDistribution, Constant, Cubic, DistributedStatisticalModel, FCDF, HollingI, HollingII, HollingIII, Linear, MichaelisMenten, NormPDF, OdeModel, Quadratic, XppOdeStatisticalModel
```
public abstract class StatisticalModel
extends AbstractFunction
implements DeclaredParameters, DeclaredVariables, Nameable, Likelihood, OptimizableScalar, FigureReportable, ObjectSamplerClient
```
This is a class which implements NamedParameters can make predictions as a function of those parameters and can have its parameters optimized. Note only the parameters in Params will be optimized by say MCMC. Note that the PosteriorParams and PriorParams are not parameters in the traditional sense but are augments/options required for evaluation of the Prior and Posterior likelihoods etc. Very often these will be left empty but can be useful when using importance sampling techniques etc.

Field Summary

Fields
Modifier and Type	Field and Description
`protected DataSetAdapter`	`adapter`
`protected java.util.HashMap`	`FigureReporters`
`protected boolean`	`invertParameterDeclarations`
`static int`	`LIKELIHOOD`
`static int`	`NEG_LOG_LIKELIHOOD`
`protected java.util.HashMap`	`paramListeners`
`protected DblParamSet`	`Params`
`protected DblParamSet`	`PosteriorParams`
`static int`	`PREDICTION`
`protected java.util.HashMap`	`priorParamListeners`
`protected DblParamSet`	`PriorParams`
`static int`	`SUM_NEG_LOG_LIKELIHOOD`
`protected boolean`	`usingDataSet`

Fields inherited from class com.mockturtlesolutions.snifflib.functions.AbstractFunction
domainDimension, rangeDimension

Constructor Summary

Constructors
Constructor and Description

StatisticalModel()

StatisticalModel(DataSet S)

StatisticalModel(DblMatrix[] X, DblMatrix Y)

Constructors
Constructor and Description
`StatisticalModel()`
`StatisticalModel(DataSet S)`
`StatisticalModel(DblMatrix[] X, DblMatrix Y)`

Method Summary

Methods
Modifier and Type	Method and Description
`abstract java.lang.String`	`about()` Return a string giving some descriptive information about the model.
`void`	`addFigureReporter(java.lang.String key, FigureReporter rep)`
`void`	`addObjectToSample(java.lang.String s)` Specifies that the object should be sampled.
`void`	`addParameterChangeListener(java.lang.String parameter, ParameterChangeListener listener)`
`protected boolean`	`declareIfNotParameter(java.lang.String p, DblMatrix v)` Convenience method that declares a parameter and sets a initial (default) value for that parameter only if the parameter is not already declared.
`protected boolean`	`declareIfNotPriorParameter(java.lang.String p, DblMatrix v)` Convenience method that declares a parameter and sets a initial (default) value for that parameter only if the parameter is not already declared.
`void`	`declareParameter(java.lang.String p)`
`void`	`declareParameter(java.lang.String p, DblMatrix v)` Convenience method that declares a parameter and sets a initial (default) value for that parameter.
`protected void`	`declarePriorParameter(java.lang.String p)`
`protected void`	`declarePriorParameter(java.lang.String p, DblMatrix v)` Convenience method that declares a parameter and sets a initial (default) value for that parameter.
`void`	`declareVariable(java.lang.String var)`
`protected void`	`fireParameterAdded(java.lang.String param)`
`protected void`	`fireParameterRemoved(java.lang.String param)`
`protected void`	`fireParameterValueChanged(java.lang.String param)`
`protected void`	`fireParameterValuesChanged()` Notifies all registered ParameterChangeListeners that all parameters have changed.
`protected void`	`firePriorParameterAdded(java.lang.String param)`
`protected void`	`firePriorParameterRemoved(java.lang.String param)`
`protected void`	`firePriorParameterValueChanged(java.lang.String param)`
`protected void`	`firePriorParameterValuesChanged()` Notifies all registered ParameterChangeListeners that all parameters have changed.
`DataSet`	`getDataAugment()`
`DataSet`	`getDataSet()`
`DataSetAdapter`	`getDataSetAdapter()`
`java.util.Set`	`getDeclaredParameters()`
`java.util.Set`	`getDeclaredPriorParameters()`
`java.util.Set`	`getDeclaredVariables()`
`FigureReporter`	`getFigureReporter(java.lang.String key)`
`java.util.Set`	`getFigureReporters()`
`boolean`	`getIgnoreNaN()`
`DblMatrix`	`getMSE()` Returns the MSE.
`java.lang.String`	`getName()`
`java.lang.Object`	`getNewObjectSample(java.lang.String f)` Returns new object sample for the named object.
`java.util.HashMap`	`getNewObjectSamples()` Returns new object samples
`java.lang.String[]`	`getObjectSamplingOffered()`
`java.lang.String[]`	`getObjectsToSample()` Gets a list of objects that are to be sampled.
`DblMatrix`	`getParam(java.lang.String name)`
`DblParamSet`	`getParams()`
`DblMatrix`	`getPosteriorParam(java.lang.String name)`
`DblParamSet`	`getPosteriorParams()` Get special (options) parameters needed to evaluate the posterior.
`abstract DblMatrix`	`getPredictionAt(DblMatrix[] X)`
`DblMatrix`	`getPriorParam(java.lang.String name)`
`DblParamSet`	`getPriorParams()`
`DblMatrix`	`getValueAt(DblMatrix Y)`
`DblMatrix`	`getValueAt(DblMatrix[] X)`
`DblMatrix`	`getValueAt(DblParamSet P)`
`DblMatrix`	`getValueToMinimize()`
`DblMatrix[]`	`getX()`
`DblMatrix`	`getY()`
`boolean`	`hasParameter(java.lang.String p)`
`boolean`	`hasPriorParameter(java.lang.String p)`
`void`	`invertParameterDeclarations(boolean s)` Inverts the logic of declareParameter method(s) so that parameters are revoked instead.
`boolean`	`isSamplingObject(java.lang.String s)` Returns true if the object is to be sampled.
`boolean`	`isVectorBased()` Returns true if the data supporting this statistical model are in the form of vectors (DblMatrix).
`DblMatrix`	`likelihood()` Returns the default likelihood of zero.
`void`	`mapName(java.lang.String modelvariable, java.lang.String datasetcolname)`
`DblMatrix`	`negLogLikelihood()` Returns the default negative log likelihood of INF.
`DblParamSet`	`negLogPrior()` Returns the negative log of the prior probability of the current parameter set.
`int`	`numParams()` Return the number of parameters.
`void`	`offerObjectSamplingFor(java.lang.String s)` Any StatisticalModel can add to the object sampling it provides by name.
`boolean`	`offersObjectSamplingFor(java.lang.String s)` Returns true if this model offers object sampling for the given string.
`java.lang.String[]`	`parameterSet()`
`void`	`putNewObjectSample(java.lang.String objName, java.lang.Object obj)`
`void`	`removeAllParameterChangeListener(java.lang.String parameter)`
`void`	`removeFigureReporter(java.lang.String key)`
`void`	`removeObjectToSample(java.lang.String s)` Specifies that the object should no longer be sampled.
`void`	`removeParameterChangeListener(java.lang.String parameter, ParameterChangeListener listener)`
`void`	`replaceParams(DblParamSet X)` Replace parameters with those in X.
`void`	`replacePosteriorParams(DblParamSet P)` Replace special (options) parameters needed to evaluate the posterior.
`void`	`replacePriorParams(DblParamSet P)`
`DblMatrix`	`residuals()` Returns the default residual of zero.
`void`	`revokeObjectSamplingFor(java.lang.String s)` Any StatisticalModel can remove the object sampling it provides by name.
`void`	`revokeParameter(java.lang.String p)`
`void`	`revokePriorParameter(java.lang.String p)`
`void`	`revokeVariable(java.lang.String var)`
`DblParamSet`	`samplePosterior()` Returns a sample from the posterior distribution of the parameters.
`DblParamSet`	`samplePosterior(java.lang.String[] subset)` Returns a sample from the posterior distribution of the given subset of parameters.
`void`	`setDataAugment(DataSet S)`
`void`	`setDataSet(DataSet F)`
`void`	`setIgnoreNaN(boolean x)`
`void`	`setName(java.lang.String n)`
`void`	`setObjectsToSample(java.lang.String[] S)` Specifies that the object should be sampled.
`void`	`setParam(java.lang.String name, DblMatrix value)`
`void`	`setParams(DblParamSet P)`
`void`	`setPosteriorParam(java.lang.String name, DblMatrix value)`
`void`	`setPosteriorParams(DblParamSet P)` Set special (options) parameters needed to evaluate the posterior.
`void`	`setPriorParam(java.lang.String name, DblMatrix value)`
`void`	`setPriorParams(DblParamSet P)`
`void`	`setValueToGet(int f)`
`void`	`setX(DblMatrix[] X)`
`void`	`setY(DblMatrix Y)`
`DblMatrix`	`sumNegLogLikelihood()` Return the sum of the negative log likelihood
`void`	`unMapName(java.lang.String modelvariable)`
`java.lang.String[]`	`variableSet()`

Methods inherited from class com.mockturtlesolutions.snifflib.functions.AbstractFunction
domainDimension, plotOver, plotOver, rangeDimension

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Field Detail
  - Params
```
protected DblParamSet Params
```
  - adapter
```
protected DataSetAdapter adapter
```
  - PosteriorParams
```
protected DblParamSet PosteriorParams
```
  - PriorParams
```
protected DblParamSet PriorParams
```
  - usingDataSet
```
protected boolean usingDataSet
```
  - paramListeners
```
protected java.util.HashMap paramListeners
```
  - priorParamListeners
```
protected java.util.HashMap priorParamListeners
```
  - FigureReporters
```
protected java.util.HashMap FigureReporters
```
  - invertParameterDeclarations
```
protected boolean invertParameterDeclarations
```
  - NEG_LOG_LIKELIHOOD
```
public static final int NEG_LOG_LIKELIHOOD
```
    See Also:
    Constant Field Values
  - LIKELIHOOD
```
public static final int LIKELIHOOD
```
    See Also:
    Constant Field Values
  - SUM_NEG_LOG_LIKELIHOOD
```
public static final int SUM_NEG_LOG_LIKELIHOOD
```
    See Also:
    Constant Field Values
  - PREDICTION
```
public static final int PREDICTION
```
    See Also:
    Constant Field Values
- Constructor Detail
  - StatisticalModel
```
public StatisticalModel()
```
  - StatisticalModel
```
public StatisticalModel(DataSet S)
```
  - StatisticalModel
```
public StatisticalModel(DblMatrix[] X,
                DblMatrix Y)
```
- Method Detail
  - putNewObjectSample
```
public void putNewObjectSample(java.lang.String objName,
                      java.lang.Object obj)
```
  - addFigureReporter
```
public void addFigureReporter(java.lang.String key,
                     FigureReporter rep)
```
    Specified by:
    
    addFigureReporter in interface FigureReportable
  - removeFigureReporter
```
public void removeFigureReporter(java.lang.String key)
```
    Specified by:
    
    removeFigureReporter in interface FigureReportable
  - getFigureReporter
```
public FigureReporter getFigureReporter(java.lang.String key)
```
    Specified by:
    
    getFigureReporter in interface FigureReportable
  - getFigureReporters
```
public java.util.Set getFigureReporters()
```
    Specified by:
    
    getFigureReporters in interface FigureReportable
  - getNewObjectSamples
```
public java.util.HashMap getNewObjectSamples()
```
    Returns new object samples
    
    Specified by:
    
    getNewObjectSamples in interface ObjectSamplerClient
  - getNewObjectSample
```
public java.lang.Object getNewObjectSample(java.lang.String f)
```
    Returns new object sample for the named object.
    
    Specified by:
    
    getNewObjectSample in interface ObjectSamplerClient
  - getObjectsToSample
```
public java.lang.String[] getObjectsToSample()
```
    Gets a list of objects that are to be sampled.
    
    Specified by:
    
    getObjectsToSample in interface ObjectSampler
  - setObjectsToSample
```
public void setObjectsToSample(java.lang.String[] S)
```
    Specifies that the object should be sampled. This is equivalent to calling addObjectToSample on each element of the String[].
    
    Specified by:
    
    setObjectsToSample in interface ObjectSampler
  - addObjectToSample
```
public void addObjectToSample(java.lang.String s)
```
    Specifies that the object should be sampled. Valid inputs are the strings returned by the model's getObjectsToSample() and are verifiable with offersObjectSamplingFor or listed in the output of getOfferedObjectSampling.
    
    Specified by:
    
    addObjectToSample in interface ObjectSampler
  - removeObjectToSample
```
public void removeObjectToSample(java.lang.String s)
```
    Specifies that the object should no longer be sampled.
    
    Specified by:
    
    removeObjectToSample in interface ObjectSampler
  - isSamplingObject
```
public boolean isSamplingObject(java.lang.String s)
```
    Returns true if the object is to be sampled.
    
    Specified by:
    
    isSamplingObject in interface ObjectSampler
  - offersObjectSamplingFor
```
public boolean offersObjectSamplingFor(java.lang.String s)
```
    Returns true if this model offers object sampling for the given string. Just because a model offers sampling for a particular object does not mean that sampling will take place. Sampling actually carried out is mandated through the setObjectsToSample and/or addObjectToSample methods and can be verified through the samplesObject() method.
    
    Specified by:
    
    offersObjectSamplingFor in interface ObjectSamplerClient
  - offerObjectSamplingFor
```
public void offerObjectSamplingFor(java.lang.String s)
```
    Any StatisticalModel can add to the object sampling it provides by name.
    
    Specified by:
    
    offerObjectSamplingFor in interface ObjectSamplerClient
  - revokeObjectSamplingFor
```
public void revokeObjectSamplingFor(java.lang.String s)
```
    Any StatisticalModel can remove the object sampling it provides by name.
    
    Specified by:
    
    revokeObjectSamplingFor in interface ObjectSamplerClient
  - getObjectSamplingOffered
```
public java.lang.String[] getObjectSamplingOffered()
```
    Specified by:
    
    getObjectSamplingOffered in interface ObjectSamplerClient
  - fireParameterValuesChanged
```
protected void fireParameterValuesChanged()
```
    Notifies all registered ParameterChangeListeners that all parameters have changed.
  - fireParameterValueChanged
```
protected void fireParameterValueChanged(java.lang.String param)
```
  - fireParameterAdded
```
protected void fireParameterAdded(java.lang.String param)
```
  - fireParameterRemoved
```
protected void fireParameterRemoved(java.lang.String param)
```
  - firePriorParameterValuesChanged
```
protected void firePriorParameterValuesChanged()
```
    Notifies all registered ParameterChangeListeners that all parameters have changed.
  - firePriorParameterValueChanged
```
protected void firePriorParameterValueChanged(java.lang.String param)
```
  - firePriorParameterAdded
```
protected void firePriorParameterAdded(java.lang.String param)
```
  - firePriorParameterRemoved
```
protected void firePriorParameterRemoved(java.lang.String param)
```
  - invertParameterDeclarations
```
public void invertParameterDeclarations(boolean s)
```
    Inverts the logic of declareParameter method(s) so that parameters are revoked instead. This method can be useful when writing code that "automatically" configures and unconfigures model parameters.
  - declarePriorParameter
```
protected void declarePriorParameter(java.lang.String p)
```
  - declarePriorParameter
```
protected void declarePriorParameter(java.lang.String p,
                         DblMatrix v)
```
    Convenience method that declares a parameter and sets a initial (default) value for that parameter.
  - declareIfNotPriorParameter
```
protected boolean declareIfNotPriorParameter(java.lang.String p,
                                 DblMatrix v)
```
    Convenience method that declares a parameter and sets a initial (default) value for that parameter only if the parameter is not already declared.
  - getDeclaredPriorParameters
```
public java.util.Set getDeclaredPriorParameters()
```
  - revokePriorParameter
```
public void revokePriorParameter(java.lang.String p)
```
  - declareParameter
```
public void declareParameter(java.lang.String p)
```
    Specified by:
    
    declareParameter in interface DeclaredParameters
  - declareParameter
```
public void declareParameter(java.lang.String p,
                    DblMatrix v)
```
    Convenience method that declares a parameter and sets a initial (default) value for that parameter.
  - declareIfNotParameter
```
protected boolean declareIfNotParameter(java.lang.String p,
                            DblMatrix v)
```
    Convenience method that declares a parameter and sets a initial (default) value for that parameter only if the parameter is not already declared.
  - getDeclaredParameters
```
public java.util.Set getDeclaredParameters()
```
    Specified by:
    
    getDeclaredParameters in interface DeclaredParameters
  - revokeParameter
```
public void revokeParameter(java.lang.String p)
```
    Specified by:
    
    revokeParameter in interface DeclaredParameters
  - getDeclaredVariables
```
public java.util.Set getDeclaredVariables()
```
    Specified by:
    
    getDeclaredVariables in interface DeclaredVariables
  - declareVariable
```
public void declareVariable(java.lang.String var)
```
    Specified by:
    
    declareVariable in interface DeclaredVariables
  - revokeVariable
```
public void revokeVariable(java.lang.String var)
```
    Specified by:
    
    revokeVariable in interface DeclaredVariables
  - getDataSetAdapter
```
public DataSetAdapter getDataSetAdapter()
```
  - setName
```
public void setName(java.lang.String n)
```
    Specified by:
    
    setName in interface Nameable
  - getName
```
public java.lang.String getName()
```
    Specified by:
    
    getName in interface Nameable
  - getPosteriorParams
```
public DblParamSet getPosteriorParams()
```
    Get special (options) parameters needed to evaluate the posterior.
  - setPosteriorParams
```
public void setPosteriorParams(DblParamSet P)
```
    Set special (options) parameters needed to evaluate the posterior.
  - replacePosteriorParams
```
public void replacePosteriorParams(DblParamSet P)
```
    Replace special (options) parameters needed to evaluate the posterior.
  - samplePosterior
```
public DblParamSet samplePosterior()
```
    Returns a sample from the posterior distribution of the parameters. This default implementation returns the current parameter set.
  - samplePosterior
```
public DblParamSet samplePosterior(java.lang.String[] subset)
```
    Returns a sample from the posterior distribution of the given subset of parameters. Subset of parameters are given as a Vector of Strings. This default implementation returns the current parameter set.
  - negLogPrior
```
public DblParamSet negLogPrior()
```
    Returns the negative log of the prior probability of the current parameter set. This default implementation assumes a prior probability of 1 for each parameter resulting in a return value of zero. Method should be over-riden for other priors.
  - getPriorParams
```
public DblParamSet getPriorParams()
```
  - setPriorParams
```
public void setPriorParams(DblParamSet P)
```
  - replacePriorParams
```
public void replacePriorParams(DblParamSet P)
```
  - hasParameter
```
public boolean hasParameter(java.lang.String p)
```
    Specified by:
    
    hasParameter in interface NamedParameters
  - hasPriorParameter
```
public boolean hasPriorParameter(java.lang.String p)
```
  - getParams
```
public DblParamSet getParams()
```
  - setParams
```
public void setParams(DblParamSet P)
```
  - setValueToGet
```
public void setValueToGet(int f)
```
  - setDataAugment
```
public void setDataAugment(DataSet S)
```
  - getDataAugment
```
public DataSet getDataAugment()
```
  - isVectorBased
```
public boolean isVectorBased()
```
    Returns true if the data supporting this statistical model are in the form of vectors (DblMatrix). Otherwise they are assumed to be supported by a DataSet instance.
  - setX
```
public void setX(DblMatrix[] X)
```
  - setY
```
public void setY(DblMatrix Y)
```
  - mapName
```
public void mapName(java.lang.String modelvariable,
           java.lang.String datasetcolname)
```
  - unMapName
```
public void unMapName(java.lang.String modelvariable)
```
  - setDataSet
```
public void setDataSet(DataSet F)
```
  - getDataSet
```
public DataSet getDataSet()
```
  - getX
```
public DblMatrix[] getX()
```
  - getY
```
public DblMatrix getY()
```
  - setIgnoreNaN
```
public void setIgnoreNaN(boolean x)
```
  - getIgnoreNaN
```
public boolean getIgnoreNaN()
```
  - residuals
```
public DblMatrix residuals()
```
    Returns the default residual of zero. This method should be over-ridden by extending classes.
  - getMSE
```
public DblMatrix getMSE()
```
    Returns the MSE.
  - likelihood
```
public DblMatrix likelihood()
```
    Returns the default likelihood of zero. This method should be over-ridden by extending classes.
    
    Specified by:
    
    likelihood in interface Likelihood
  - negLogLikelihood
```
public DblMatrix negLogLikelihood()
```
    Returns the default negative log likelihood of INF. This method should be over-ridden by extending classes.
    
    Specified by:
    
    negLogLikelihood in interface Likelihood
  - sumNegLogLikelihood
```
public DblMatrix sumNegLogLikelihood()
```
    Return the sum of the negative log likelihood
  - getPredictionAt
```
public abstract DblMatrix getPredictionAt(DblMatrix[] X)
```
  - getValueAt
```
public DblMatrix getValueAt(DblMatrix Y)
```
    Specified by:
    
    getValueAt in interface OptimizableScalar
    
    Specified by:
    
    getValueAt in class AbstractFunction
  - getValueAt
```
public DblMatrix getValueAt(DblMatrix[] X)
```
    Specified by:
    
    getValueAt in class AbstractFunction
  - getValueAt
```
public DblMatrix getValueAt(DblParamSet P)
```
  - addParameterChangeListener
```
public void addParameterChangeListener(java.lang.String parameter,
                              ParameterChangeListener listener)
```
  - removeParameterChangeListener
```
public void removeParameterChangeListener(java.lang.String parameter,
                                 ParameterChangeListener listener)
```
  - removeAllParameterChangeListener
```
public void removeAllParameterChangeListener(java.lang.String parameter)
```
  - getParam
```
public DblMatrix getParam(java.lang.String name)
```
    Specified by:
    
    getParam in interface NamedParameters
  - setParam
```
public void setParam(java.lang.String name,
            DblMatrix value)
```
    Specified by:
    
    setParam in interface NamedParameters
  - getPosteriorParam
```
public DblMatrix getPosteriorParam(java.lang.String name)
```
  - setPosteriorParam
```
public void setPosteriorParam(java.lang.String name,
                     DblMatrix value)
```
  - getPriorParam
```
public DblMatrix getPriorParam(java.lang.String name)
```
  - setPriorParam
```
public void setPriorParam(java.lang.String name,
                 DblMatrix value)
```
  - replaceParams
```
public void replaceParams(DblParamSet X)
```
    Replace parameters with those in X. Note only the parameters in X will be modified. Any other parameters will remain unmodified.
    
    Specified by:
    
    replaceParams in interface NamedParameters
  - variableSet
```
public java.lang.String[] variableSet()
```
  - parameterSet
```
public java.lang.String[] parameterSet()
```
    Specified by:
    
    parameterSet in interface NamedParameters
  - numParams
```
public int numParams()
```
    Return the number of parameters.
  - getValueToMinimize
```
public DblMatrix getValueToMinimize()
```
    Specified by:
    
    getValueToMinimize in interface OptimizableScalar
  - about
```
public abstract java.lang.String about()
```
    Return a string giving some descriptive information about the model.

Class StatisticalModel

Field Summary

Fields inherited from class com.mockturtlesolutions.snifflib.functions.AbstractFunction

Constructor Summary

Method Summary

Methods inherited from class com.mockturtlesolutions.snifflib.functions.AbstractFunction

Methods inherited from class java.lang.Object

Field Detail

Params

adapter

PosteriorParams

PriorParams

usingDataSet

paramListeners

priorParamListeners

FigureReporters

invertParameterDeclarations

NEG_LOG_LIKELIHOOD

LIKELIHOOD

SUM_NEG_LOG_LIKELIHOOD

PREDICTION

Constructor Detail

StatisticalModel

StatisticalModel

StatisticalModel

Method Detail

putNewObjectSample

addFigureReporter

removeFigureReporter

getFigureReporter

getFigureReporters

getNewObjectSamples

getNewObjectSample

getObjectsToSample

setObjectsToSample

addObjectToSample

removeObjectToSample

isSamplingObject

offersObjectSamplingFor

offerObjectSamplingFor

revokeObjectSamplingFor

getObjectSamplingOffered

fireParameterValuesChanged

fireParameterValueChanged

fireParameterAdded

fireParameterRemoved

firePriorParameterValuesChanged

firePriorParameterValueChanged

firePriorParameterAdded

firePriorParameterRemoved

invertParameterDeclarations

declarePriorParameter

declarePriorParameter

declareIfNotPriorParameter

getDeclaredPriorParameters

revokePriorParameter

declareParameter

declareParameter

declareIfNotParameter

getDeclaredParameters

revokeParameter

getDeclaredVariables

declareVariable

revokeVariable

getDataSetAdapter

setName

getName

getPosteriorParams

setPosteriorParams

replacePosteriorParams

samplePosterior

samplePosterior

negLogPrior

getPriorParams

setPriorParams

replacePriorParams

hasParameter

hasPriorParameter

getParams

setParams