com.mockturtlesolutions.snifflib.invprobs

Class BayesianLinear

java.lang.Object

com.mockturtlesolutions.snifflib.functions.AbstractFunction

com.mockturtlesolutions.snifflib.invprobs.StatisticalModel

com.mockturtlesolutions.snifflib.testfun.Linear

com.mockturtlesolutions.snifflib.invprobs.BayesianLinear

All Implemented Interfaces:

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

public class BayesianLinear
extends Linear

This is a simple extension of Linear appropriate for full Bayesian linear regression under the assumption of independent and identically distributed Gaussian errors and uniform prior. The parameter sigma has been added which represents the standard deviation of the residuals.

Field Summary

Fields

Modifier and Type	Field and Description
protected NormalDistribution	normal

Fields inherited from class com.mockturtlesolutions.snifflib.invprobs.StatisticalModel

adapter, FigureReporters, invertParameterDeclarations, LIKELIHOOD, NEG_LOG_LIKELIHOOD, paramListeners, Params, PosteriorParams, PREDICTION, priorParamListeners, PriorParams, SUM_NEG_LOG_LIKELIHOOD, usingDataSet

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

domainDimension, rangeDimension

Constructor Summary

Constructors

Constructor and Description
BayesianLinear()

Method Summary

Methods

Modifier and Type	Method and Description
DblMatrix	negLogLikelihood() Returns the default negative log likelihood of INF.

Methods inherited from class com.mockturtlesolutions.snifflib.testfun.Linear

about, getPredictionAt, residuals

Methods inherited from class com.mockturtlesolutions.snifflib.invprobs.StatisticalModel

addFigureReporter, addObjectToSample, addParameterChangeListener, declareIfNotParameter, declareIfNotPriorParameter, declareParameter, declareParameter, declarePriorParameter, declarePriorParameter, declareVariable, fireParameterAdded, fireParameterRemoved, fireParameterValueChanged, fireParameterValuesChanged, firePriorParameterAdded, firePriorParameterRemoved, firePriorParameterValueChanged, firePriorParameterValuesChanged, getDataAugment, getDataSet, getDataSetAdapter, getDeclaredParameters, getDeclaredPriorParameters, getDeclaredVariables, getFigureReporter, getFigureReporters, getIgnoreNaN, getMSE, getName, getNewObjectSample, getNewObjectSamples, getObjectSamplingOffered, getObjectsToSample, getParam, getParams, getPosteriorParam, getPosteriorParams, getPriorParam, getPriorParams, getValueAt, getValueAt, getValueAt, getValueToMinimize, getX, getY, hasParameter, hasPriorParameter, invertParameterDeclarations, isSamplingObject, isVectorBased, likelihood, mapName, negLogPrior, numParams, offerObjectSamplingFor, offersObjectSamplingFor, parameterSet, putNewObjectSample, removeAllParameterChangeListener, removeFigureReporter, removeObjectToSample, removeParameterChangeListener, replaceParams, replacePosteriorParams, replacePriorParams, revokeObjectSamplingFor, revokeParameter, revokePriorParameter, revokeVariable, samplePosterior, samplePosterior, setDataAugment, setDataSet, setIgnoreNaN, setName, setObjectsToSample, setParam, setParams, setPosteriorParam, setPosteriorParams, setPriorParam, setPriorParams, setValueToGet, setX, setY, sumNegLogLikelihood, unMapName, 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

normal

protected NormalDistribution normal

Constructor Detail

BayesianLinear

public BayesianLinear()

Method Detail

negLogLikelihood

public DblMatrix negLogLikelihood()

Description copied from class: StatisticalModel

Returns the default negative log likelihood of INF. This method should be over-ridden by extending classes.

Specified by:

negLogLikelihood in interface Likelihood

Overrides:

negLogLikelihood in class StatisticalModel