com.mockturtlesolutions.snifflib.testfun

Class MichaelisMenten

java.lang.Object

com.mockturtlesolutions.snifflib.functions.AbstractFunction

com.mockturtlesolutions.snifflib.invprobs.StatisticalModel

com.mockturtlesolutions.snifflib.testfun.MichaelisMenten

All Implemented Interfaces:

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

public class MichaelisMenten
extends StatisticalModel

Field Summary

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
MichaelisMenten()

Method Summary

Methods

Modifier and Type	Method and Description
java.lang.String	about() Return a string giving some descriptive information about the model.
DblMatrix	getPredictionAt(DblMatrix[] X)
DblMatrix	negLogLikelihood() Provides negative log likelihood for Michaelis-Menten using the assumption of i.i.d Gaussian errors.

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, residuals, 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

Constructor Detail

MichaelisMenten

public MichaelisMenten()

Method Detail

negLogLikelihood

public DblMatrix negLogLikelihood()

Provides negative log likelihood for Michaelis-Menten using the assumption of i.i.d Gaussian errors.

Specified by:

negLogLikelihood in interface Likelihood

Overrides:

negLogLikelihood in class StatisticalModel

getPredictionAt

public DblMatrix getPredictionAt(DblMatrix[] X)

Specified by:

getPredictionAt in class StatisticalModel

about

public java.lang.String about()

Description copied from class: StatisticalModel

Return a string giving some descriptive information about the model.

Specified by:

about in class StatisticalModel