&,Stopping,Stopping-method
                        The method combining two atomic stopping rules
&,Stopping,StoppingAll-method
                        The method combining an atomic and a stopping
                        list
&,StoppingAll,Stopping-method
                        The method combining a stopping list and an
                        atomic
AllModels-class         Class for All models This is a class where all
                        models inherit.
CohortSize-class        The virtual class for cohort sizes
CohortSizeConst         Initialization function for "CohortSizeConst"
CohortSizeConst-class   Constant cohort size
CohortSizeDLT           Initialization function for "CohortSizeDLT"
CohortSizeDLT-class     Cohort size based on number of DLTs
CohortSizeMax           Initialization function for "CohortSizeMax"
CohortSizeMax-class     Size based on maximum of multiple cohort size
                        rules
CohortSizeMin           Initialization function for "CohortSizeMin"
CohortSizeMin-class     Size based on minimum of multiple cohort size
                        rules
CohortSizeParts         Initialization function for "CohortSizeParts"
CohortSizeParts-class   Cohort size based on the parts
CohortSizeRange         Initialization function for "CohortSizeRange"
CohortSizeRange-class   Cohort size based on dose range
Data                    Initialization function for the "Data" class
Data-class              Class for the data input
DataDual                Initialization function for the "DataDual"
                        class
DataDual-class          Class for the dual endpoint data input
DataMixture             Initialization function for the "DataMixture"
                        class
DataMixture-class       Class for the data with mixture sharing
DataParts               Initialization function for the "DataParts"
                        class
DataParts-class         Class for the data with two study parts
Design                  Initialization function for "Design"
Design-class            Class for the CRM design
DualDesign              Initialization function for "DualDesign"
DualDesign-class        Class for the dual-endpoint CRM design
DualEndpoint            Initialization function for the "DualEndpoint"
                        class
DualEndpoint-class      General class for the dual endpoint model
DualEndpointBeta        Initialization function for the
                        "DualEndpointBeta" class
DualEndpointBeta-class
                        Dual endpoint model with beta function for
                        dose-biomarker relationship
DualEndpointEmax        Initialization function for the
                        "DualEndpointEmax" class
DualEndpointEmax-class
                        Dual endpoint model with emax function for
                        dose-biomarker relationship
DualEndpointRW          Initialization function for the
                        "DualEndpointRW" class
DualEndpointRW-class    Dual endpoint model with RW prior for biomarker
DualResponsesDesign     Initialization function for
                        'DualResponsesDesign"
DualResponsesDesign-class
                        This is a class of design based on DLE
                        responses using the 'LogisticIndepBeta' model
                        model and efficacy responses using 'ModelEff'
                        model class without DLE and efficacy samples.
                        It contain all slots in 'RuleDesign' and
                        'TDDesign' class object
DualResponsesSamplesDesign
                        Initialization function for
                        'DualResponsesSamplesDesign"
DualResponsesSamplesDesign-class
                        This is a class of design based on DLE
                        responses using the 'LogisticIndepBeta' model
                        model and efficacy responses using 'ModelEff'
                        model class with DLE and efficacy samples.It
                        contain all slots in 'RuleDesign' and
                        'TDsamplesDesign' class object
DualSimulations         Initialization function for "DualSimulations"
DualSimulations-class   Class for the simulations output from
                        dual-endpoint model based designs
DualSimulationsSummary-class
                        Class for the summary of dual-endpoint
                        simulations output
EffFlexi                Initialization function for the "EffFlexi"
                        class
EffFlexi-class          Class for the efficacy model in flexible form
                        for prior expressed in form of pseudo data
Effloglog               Initialization function for the "Effloglog"
                        class
Effloglog-class         Class for the linear log-log efficacy model
                        using pseudo data prior
ExpEff                  Compute the expected efficacy based on a given
                        dose, a given pseudo Efficacy log-log model and
                        a given efficacy sample
GeneralData-class       Class for general data input
GeneralModel-class      No Intitialization function for this General
                        class for model input
GeneralSimulations      Initialization function for
                        "GeneralSimulations"
GeneralSimulations-class
                        General class for the simulations output
GeneralSimulationsSummary-class
                        Class for the summary of general simulations
                        output
Increments-class        The virtual class for controlling increments
IncrementsRelative      Initialization function for
                        "IncrementsRelative"
IncrementsRelative-class
                        Increments control based on relative
                        differences in intervals
IncrementsRelativeDLT   Initialization function for
                        "IncrementsRelativeDLT"
IncrementsRelativeDLT-class
                        Increments control based on relative
                        differences in terms of DLTs
IncrementsRelativeParts
                        Initialization function for
                        "IncrementsRelativeParts"
IncrementsRelativeParts-class
                        Increments control based on relative
                        differences in intervals, with special rules
                        for part 1 and beginning of part 2
LogisticIndepBeta       Intialization function for "LogisticIndepBeta"
                        class
LogisticIndepBeta-class
                        No initialization function Standard logistic
                        model with prior in form of pseudo data
LogisticKadane          Initialization function for the
                        "LogisticKadane" class
LogisticKadane-class    Reparametrized logistic model
LogisticLogNormal       Initialization function for the
                        "LogisticLogNormal" class
LogisticLogNormal-class
                        Standard logistic model with bivariate (log)
                        normal prior
LogisticLogNormalMixture
                        Initialization function for the
                        "LogisticLogNormalMixture" class
LogisticLogNormalMixture-class
                        Standard logistic model with online mixture of
                        two bivariate log normal priors
LogisticLogNormalSub    Initialization function for the
                        "LogisticLogNormalSub" class
LogisticLogNormalSub-class
                        Standard logistic model with bivariate (log)
                        normal prior with substractive dose
                        standardization
LogisticNormal          Initialization function for the
                        "LogisticNormal" class
LogisticNormal-class    Standard logistic model with bivariate normal
                        prior
LogisticNormalFixedMixture
                        Initialization function for the
                        "LogisticNormalFixedMixture" class
LogisticNormalFixedMixture-class
                        Standard logistic model with fixed mixture of
                        multiple bivariate (log) normal priors
LogisticNormalMixture   Initialization function for the
                        "LogisticNormalMixture" class
LogisticNormalMixture-class
                        Standard logistic model with flexible mixture
                        of two bivariate normal priors
McmcOptions             Initialization function for the "McmcOptions"
                        class
McmcOptions-class       Class for the three canonical MCMC options
MinimalInformative      Construct a minimally informative prior
Model-class             Class for the model input
ModelEff-class          No Initialization function class for Efficacy
                        models using pseudo data prior
ModelPseudo-class       Class of models using expressing their prior in
                        form of Pseudo data
ModelTox-class          No intialization function Class for DLE models
                        using pseudo data prior. This is a class of DLE
                        (dose-limiting events) models/ toxicity model
                        which contains all DLE models for which their
                        prior are specified in form of pseudo data (as
                        if there is some data before the trial starts).
                        It inherits all slots from 'ModelPseudo'
NextBest-class          The virtual class for finding next best dose
NextBestDualEndpoint    Initialization function for
                        "NextBestDualEndpoint"
NextBestDualEndpoint-class
                        The class with the input for finding the next
                        dose based on the dual endpoint model
NextBestMTD             Initialization function for class "NextBestMTD"
NextBestMTD-class       The class with the input for finding the next
                        best MTD estimate
NextBestMaxGain         Initialization function for the class
                        'NextBestMaxGain'
NextBestMaxGain-class   Next best dose with maximum gain value based on
                        a pseudo DLE and efficacy model without samples
NextBestMaxGainSamples
                        Initialization function for class
                        "NextBestMaxGainSamples"
NextBestMaxGainSamples-class
                        Next best dose with maximum gain value based on
                        a pseudo DLE and efficacy model with samples
NextBestNCRM            Initialization function for "NextBestNCRM"
NextBestNCRM-class      The class with the input for finding the next
                        dose in target interval
NextBestTD              Initialization function for the class
                        "NextBestTD"
NextBestTD-class        Next best dose based on Pseudo DLE model
                        without sample
NextBestTDsamples       Initialization function for class
                        "NextBestTDsamples"
NextBestTDsamples-class
                        Next best dose based on Pseudo DLE Model with
                        samples
NextBestThreePlusThree
                        Initialization function for
                        "NextBestThreePlusThree"
NextBestThreePlusThree-class
                        The class with the input for finding the next
                        dose in target interval
PseudoDualFlexiSimulations
                        Initialization function for
                        'PseudoDualFlexiSimulations' class
PseudoDualFlexiSimulations-class
                        This is a class which captures the trial
                        simulations design using both the DLE and
                        efficacy responses. The design of model from
                        'ModelTox' class and the efficacy model from
                        'EffFlexi' class It contains all slots from
                        'GeneralSimulations', 'PseudoSimulations' and
                        'PseudoDualSimulations' object. In comparison
                        to the parent class 'PseudoDualSimulations', it
                        contains additional slots to capture the
                        sigma2betaW estimates.
PseudoDualSimulations   Initialization function for
                        'DualPseudoSimulations' class
PseudoDualSimulations-class
                        This is a class which captures the trial
                        simulations design using both the DLE and
                        efficacy responses. The design of model from
                        'ModelTox' class and the efficacy model from
                        'ModelEff' class (except 'EffFlexi' class). It
                        contains all slots from 'GeneralSimulations'
                        and 'PseudoSimulations' object. In comparison
                        to the parent class 'PseudoSimulations', it
                        contains additional slots to capture the
                        dose-efficacy curve and the sigma2 estimates.
PseudoDualSimulationsSummary-class
                        Class for the summary of the dual responses
                        simulations using pseudo models
PseudoSimulations       Initialization function of the
                        'PseudoSimulations' class
PseudoSimulations-class
                        This is a class which captures the trial
                        simulations from designs using pseudo model.
                        The design for DLE only responses and model
                        from 'ModelTox' class object. It contains all
                        slots from 'GeneralSimulations' object.
                        Additional slots fit and stopReasons compared
                        to the general class 'GeneralSimulations'.
PseudoSimulationsSummary-class
                        Class for the summary of pseudo-models
                        simulations output
Quantiles2LogisticNormal
                        Convert prior quantiles (lower, median, upper)
                        to logistic (log) normal model
Report                  A Reference Class to represent sequentially
                        updated reporting objects.
RuleDesign              Initialization function for "RuleDesign"
RuleDesign-class        Class for rule-based designs
Samples                 Initialization function for "Samples"
Samples-class           Class for the MCMC output
Simulations             Initialization function for the "Simulations"
                        class
Simulations-class       Class for the simulations output from model
                        based designs
SimulationsSummary-class
                        Class for the summary of model-based
                        simulations output
Stopping-class          The virtual class for stopping rules
StoppingAll             Initialization function for "StoppingAll"
StoppingAll-class       Stop based on fullfillment of all multiple
                        stopping rules
StoppingAny             Initialization function for "StoppingAny"
StoppingAny-class       Stop based on fullfillment of any stopping rule
StoppingCohortsNearDose
                        Initialization function for
                        "StoppingCohortsNearDose"
StoppingCohortsNearDose-class
                        Stop based on number of cohorts near to next
                        best dose
StoppingGstarCIRatio    Initialization function for
                        "StoppingGstarCIRatio"
StoppingGstarCIRatio-class
                        Stop based on a target ratio, the ratio of the
                        upper to the lower 95% credibility interval of
                        the estimate of the minimum of the dose which
                        gives the maximum gain (Gstar) and the TD end
                        of trial, the dose with probability of DLE
                        equals to the target probability of DLE used at
                        the end of a trial.
StoppingHighestDose     Initialization function for
                        "StoppingHighestDose"
StoppingHighestDose-class
                        Stop when the highest dose is reached
StoppingList            Initialization function for "StoppingList"
StoppingList-class      Stop based on multiple stopping rules
StoppingMTDdistribution
                        Initialization function for
                        "StoppingMTDdistribution"
StoppingMTDdistribution-class
                        Stop based on MTD distribution
StoppingMinCohorts      Initialization function for
                        "StoppingMinCohorts"
StoppingMinCohorts-class
                        Stop based on minimum number of cohorts
StoppingMinPatients     Initialization function for
                        "StoppingMinPatients"
StoppingMinPatients-class
                        Stop based on minimum number of patients
StoppingPatientsNearDose
                        Initialization function for
                        "StoppingPatientsNearDose"
StoppingPatientsNearDose-class
                        Stop based on number of patients near to next
                        best dose
StoppingTDCIRatio       Initialization function for "StoppingTDCIRatio"
StoppingTDCIRatio-class
                        Stop based on a target ratio, the ratio of the
                        upper to the lower 95% credibility interval of
                        the estimate of TD end of trial, the dose with
                        probability of DLE equals to the target
                        probability of DLE used at the end of a trial
StoppingTargetBiomarker
                        Initialization function for
                        "StoppingTargetBiomarker"
StoppingTargetBiomarker-class
                        Stop based on probability of target biomarker
StoppingTargetProb      Initialization function for
                        "StoppingTargetProb"
StoppingTargetProb-class
                        Stop based on probability of target tox
                        interval
TDDesign                Initialization function for 'TDDesign' class
TDDesign-class          Design class using DLE responses only based on
                        the pseudo DLE model without sample
TDsamplesDesign         Initialization function for 'TDsamplesDesign'
                        class
TDsamplesDesign-class   This is a class of design based only on DLE
                        responses using the 'LogisticIndepBeta' class
                        model and DLE samples are also used.  In
                        addition to the slots in the more simple
                        'RuleDesign', objects of this class contain:
ThreePlusThreeDesign    Creates a new 3+3 design object from a dose
                        grid
Validate                A Reference Class to help programming
                        validation for new S4 classes
approximate             Approximate posterior with (log) normal
                        distribution
as.list,GeneralData-method
                        as.list method for the "GeneralData" class
biomLevel               Compute the biomarker level for a given dose,
                        given model and samples
crmPack-package         Object-oriented implementation of CRM designs
crmPackExample          Open the example pdf for crmPack
crmPackHelp             Open the browser with help pages for crmPack
dose                    Compute the doses for a given probability,
                        given model and samples
examine                 Obtain hypothetical trial course table for a
                        design
fit                     Fit method for the Samples class
fitGain                 Get the fiited values for the gain values at
                        all dose levels based on a given pseudo DLE
                        model, DLE sample, a pseudo efficacy model, a
                        Efficacy sample and data. This method returns a
                        data frame with dose, middle, lower and upper
                        quantiles of the gain value samples
gain                    Compute the gain value with a given dose level,
                        given a pseudo DLE model, a DLE sample, a
                        pseudo Efficacy log-log model and a Efficacy
                        sample
get,Samples,character-method
                        Get specific parameter samples and produce a
                        data.frame
getEff                  Extracting efficacy responses for subjects
                        without or with a DLE. This is a class where we
                        separate efficacy responses with or without a
                        DLE. It outputs the efficacy responses and
                        their corresponding dose levels treated at in
                        two categories (with or without DLE)
getMinInfBeta           Get the minimal informative unimodal beta
                        distribution
initialize,DualEndpointOld-method
                        Initialization method for the "DualEndpointOld"
                        class
logit                   Shorthand for logit function
maxDose                 Determine the maximum possible next dose
maxSize                 "MAX" combination of cohort size rules
mcmc                    Obtain posterior samples for all model
                        parameters
minSize                 "MIN" combination of cohort size rules
multiplot               Multiple plot function
nextBest                Find the next best dose
or-Stopping-Stopping    The method combining two atomic stopping rules
or-Stopping-StoppingAny
                        The method combining a stopping list and an
                        atomic
or-StoppingAny-Stopping
                        The method combining an atomic and a stopping
                        list
plot,Data,ModelTox-method
                        Plot of the fitted dose-tox based with a given
                        pseudo DLE model and data without samples
plot,Data,missing-method
                        Plot method for the "Data" class
plot,DataDual,ModelEff-method
                        Plot of the fitted dose-efficacy based with a
                        given pseudo efficacy model and data without
                        samples
plot,DataDual,missing-method
                        Plot method for the "DataDual" class
plot,DualSimulations,missing-method
                        Plot dual-endpoint simulations
plot,DualSimulationsSummary,missing-method
                        Plot summaries of the dual-endpoint design
                        simulations
plot,GeneralSimulations,missing-method
                        Plot simulations
plot,GeneralSimulationsSummary,missing-method
                        Graphical display of the general simulation
                        summary
plot,PseudoDualFlexiSimulations,missing-method
                        This plot method can be applied to
                        'PseudoDualFlexiSimulations' objects in order
                        to summarize them graphically. Possible 'type's
                        of plots at the moment are: trajectory Summary
                        of the trajectory of the simulated trials
                        dosesTried Average proportions of the doses
                        tested in patients sigma2 The variance of the
                        efficacy responses sigma2betaW The variance of
                        the random walk model You can specify one or
                        both of these in the 'type' argument.
plot,PseudoDualSimulations,missing-method
                        Plot simulations
plot,PseudoDualSimulationsSummary,missing-method
                        Plot the summary of Pseudo Dual Simulations
                        summary
plot,PseudoSimulationsSummary,missing-method
                        Plot summaries of the pseudo simulations
plot,Samples,DualEndpoint-method
                        Plotting dose-toxicity and dose-biomarker model
                        fits
plot,Samples,Model-method
                        Plotting dose-toxicity model fits
plot,Samples,ModelEff-method
                        Plot the fitted dose-effcacy curve using a
                        model from 'ModelEff' class with samples
plot,Samples,ModelTox-method
                        Plot the fitted dose-DLE curve using a
                        'ModelTox' class model with samples
plot,SimulationsSummary,missing-method
                        Plot summaries of the model-based design
                        simulations
plot.gtable             Plots gtable objects
plotDualResponses       Plot of the DLE and efficacy curve side by side
                        given a DLE pseudo model, a DLE sample, an
                        efficacy pseudo model and a given efficacy
                        sample
plotGain                Plot the gain curve in addition with the
                        dose-DLE and dose-efficacy curve using a given
                        DLE pseudo model, a DLE sample, a given
                        efficacy pseudo model and an efficacy sample
prob                    Compute the probability for a given dose, given
                        model and samples
sampleSize              Compute the number of samples for a given MCMC
                        options triple
setSeed                 Helper function to set and save the RNG seed
show,DualSimulationsSummary-method
                        Show the summary of the dual-endpoint
                        simulations
show,GeneralSimulationsSummary-method
                        Show the summary of the simulations
show,PseudoDualSimulationsSummary-method
                        Show the summary of Pseudo Dual simulations
                        summary
show,PseudoSimulationsSummary-method
                        Show the summary of the simulations
show,SimulationsSummary-method
                        Show the summary of the simulations
simulate,Design-method
                        Simulate outcomes from a CRM design
simulate,DualDesign-method
                        Simulate outcomes from a dual-endpoint design
simulate,DualResponsesDesign-method
                        This is a methods to simulate dose escalation
                        procedure using both DLE and efficacy
                        responses. This is a method based on the
                        'DualResponsesDesign' where DLEmodel used are
                        of 'ModelTox' class object and efficacy model
                        used are of 'ModelEff' class object. In
                        addition, no DLE and efficacy samples are
                        involved or generated in the simulation process
simulate,DualResponsesSamplesDesign-method
                        This is a methods to simulate dose escalation
                        procedure using both DLE and efficacy
                        responses. This is a method based on the
                        'DualResponsesSamplesDesign' where DLEmodel
                        used are of 'ModelTox' class object and
                        efficacy model used are of 'ModelEff' class
                        object (special case is 'EffFlexi' class model
                        object).  In addition, DLE and efficacy samples
                        are involved or generated in the simulation
                        process
simulate,RuleDesign-method
                        Simulate outcomes from a rule-based design
simulate,TDDesign-method
                        This is a methods to simulate dose escalation
                        procedure only using the DLE responses. This is
                        a method based on the 'TDDesign' where model
                        used are of 'ModelTox' class object and no
                        samples are involved.
simulate,TDsamplesDesign-method
                        This is a methods to simulate dose escalation
                        procedure only using the DLE responses. This is
                        a method based on the 'TDsamplesDesign' where
                        model used are of 'ModelTox' class object DLE
                        samples are also used
size                    Determine the size of the next cohort
stopTrial               Stop the trial?
summary,DualSimulations-method
                        Summarize the dual-endpoint design simulations,
                        relative to given true dose-toxicity and
                        dose-biomarker curves
summary,GeneralSimulations-method
                        Summarize the simulations, relative to a given
                        truth
summary,PseudoDualFlexiSimulations-method
                        Summary for Pseudo Dual responses simulations
                        given a pseudo DLE model and the Flexible
                        efficacy model.
summary,PseudoDualSimulations-method
                        Summary for Pseudo Dual responses simulations,
                        relative to a given pseudo DLE and efficacy
                        model (except the EffFlexi class model)
summary,PseudoSimulations-method
                        Summarize the simulations, relative to a given
                        truth
summary,Simulations-method
                        Summarize the model-based design simulations,
                        relative to a given truth
update,Data-method      Update method for the "Data" class
update,DataDual-method
                        Update method for the "DataDual" class
update,DataParts-method
                        Update method for the "DataParts" class
update,EffFlexi-method
                        Update method for the 'EffFlexi' Model class.
                        This is a method to update estimates both for
                        the flexible form model and the random walk
                        model (see details in 'EffFlexi' class object)
                        when new data or new observations of responses
                        are available and added in.
update,Effloglog-method
                        Update method for the 'Effloglog' Model class.
                        This is a method to update the modal estimates
                        of the model parameters theta_1 (theta1),
                        theta_2 (theta2) and nu (nu, the precision of
                        the efficacy responses) when new data or new
                        observations of responses are available and
                        added in.
update,LogisticIndepBeta-method
                        Update method for the 'LogisticIndepBeta'Model
                        class. This is a method to update the modal
                        estimates of the model parameters phi_1 (phi1)
                        and phi_2 (phi2) when new data or new
                        observations of responses are available and
                        added in.
writeModel              Creating a WinBUGS model file
