&,Stopping,Stopping-method
                        Combine Two Stopping Rules with AND
&,Stopping,StoppingAll-method
                        Combine an Atomic Stopping Rule and a Stopping
                        List with AND
&,StoppingAll,Stopping-method
                        Combine a Stopping List and an Atomic Stopping
                        Rule with AND
.DefaultCohortSize      'CohortSize'
CohortSizeConst-class   'CohortSizeConst'
CohortSizeDLT-class     'CohortSizeDLT'
CohortSizeMax-class     'CohortSizeMax'
CohortSizeMin-class     'CohortSizeMin'
CohortSizeOrdinal-class
                        'CohortSizeOrdinal'
CohortSizeParts-class   'CohortSizeParts'
CohortSizeRange-class   'CohortSizeRange'
CrmPackClass-class      'CrmPackClass'
DADesign-class          'DADesign'
DALogisticLogNormal-class
                        'DALogisticLogNormal'
DASimulations-class     'DASimulations'
Data-class              'Data'
DataDA-class            'DataDA'
DataDual-class          'DataDual'
DataGrouped-class       'DataGrouped'
DataMixture-class       'DataMixture'
DataOrdinal-class       'DataOrdinal'
DataParts-class         'DataParts'
Design-class            'Design'
DesignGrouped-class     'DesignGrouped'
DesignOrdinal-class     'DesignOrdinal'
DualDesign-class        'DualDesign'
DualEndpoint-class      'DualEndpoint'
DualEndpointBeta-class
                        'DualEndpointBeta'
DualEndpointEmax-class
                        'DualEndpointEmax'
DualEndpointRW-class    'DualEndpointRW'
DualResponsesDesign-class
                        'DualResponsesDesign.R'
DualResponsesSamplesDesign-class
                        'DualResponsesSamplesDesign'
DualSimulations-class   'DualSimulations'
DualSimulationsSummary-class
                        'DualSimulationsSummary'
EffFlexi-class          'EffFlexi'
Effloglog-class         'Effloglog'
FractionalCRM-class     'FractionalCRM'
GeneralData-class       'GeneralData'
GeneralModel-class      'GeneralModel'
GeneralSimulations-class
                        'GeneralSimulations'
GeneralSimulationsSummary-class
                        'GeneralSimulationsSummary'
Increments-class        'Increments'
IncrementsDoseLevels-class
                        'IncrementsDoseLevels'
IncrementsHSRBeta-class
                        'IncrementsHSRBeta'
IncrementsMaxToxProb-class
                        'IncrementsMaxToxProb'
IncrementsMin-class     'IncrementsMin'
IncrementsOrdinal-class
                        'IncrementsOrdinal'
IncrementsRelative-class
                        'IncrementsRelative'
IncrementsRelativeDLT-class
                        'IncrementsRelativeDLT'
IncrementsRelativeDLTCurrent-class
                        'IncrementsRelativeDLTCurrent'
IncrementsRelativeParts-class
                        'IncrementsRelativeParts'
LogisticIndepBeta-class
                        'LogisticIndepBeta'
LogisticKadane-class    'LogisticKadane'
LogisticKadaneBetaGamma-class
                        'LogisticKadaneBetaGamma'
LogisticLogNormal-class
                        'LogisticLogNormal'
LogisticLogNormalGrouped-class
                        'LogisticLogNormalGrouped'
LogisticLogNormalMixture-class
                        'LogisticLogNormalMixture'
LogisticLogNormalOrdinal-class
                        'LogisticLogNormalOrdinal'
LogisticLogNormalSub-class
                        'LogisticLogNormalSub'
LogisticNormal-class    'LogisticNormal'
LogisticNormalFixedMixture-class
                        'LogisticNormalFixedMixture'
LogisticNormalMixture-class
                        'LogisticNormalMixture'
McmcOptions-class       'McmcOptions'
MinimalInformative      Construct a Minimally Informative Prior
ModelEff-class          'ModelEff'
ModelLogNormal-class    'ModelLogNormal'
ModelParamsNormal-class
                        'ModelParamsNormal'
ModelPseudo-class       'ModelPseudo'
ModelTox-class          'ModelTox'
NextBest-class          'NextBest'
NextBestDualEndpoint-class
                        'NextBestDualEndpoint'
NextBestEWOC-class      'NextBestEWOC'
NextBestInfTheory-class
                        'NextBestInfTheory'
NextBestMTD-class       'NextBestMTD'
NextBestMaxGain-class   'NextBestMaxGain'
NextBestMaxGainSamples-class
                        'NextBestMaxGainSamples'
NextBestMinDist-class   'NextBestMinDist'
NextBestNCRM-class      'NextBestNCRM'
NextBestNCRMLoss-class
                        'NextBestNCRMLoss'
NextBestOrdinal-class   'NextBestOrdinal'
NextBestProbMTDLTE-class
                        'NextBestProbMTDLTE'
NextBestProbMTDMinDist-class
                        'NextBestProbMTDMinDist'
NextBestTD-class        'NextBestTD'
NextBestTDsamples-class
                        'NextBestTDsamples'
NextBestThreePlusThree-class
                        'NextBestThreePlusThree'
OneParExpPrior-class    'OneParExpPrior'
OneParLogNormalPrior-class
                        'OneParLogNormalPrior'
ProbitLogNormal-class   'ProbitLogNormal'
ProbitLogNormalRel-class
                        'ProbitLogNormalRel'
PseudoDualFlexiSimulations-class
                        'PseudoDualFlexiSimulations'
PseudoDualSimulations-class
                        'PseudoDualSimulations'
PseudoDualSimulationsSummary-class
                        'PseudoDualSimulationsSummary'
PseudoSimulations-class
                        'PseudoSimulations'
PseudoSimulationsSummary-class
                        'PseudoSimulationsSummary'
Quantiles2LogisticNormal
                        Convert Prior Quantiles to Logistic (Log)
                        Normal Model
RuleDesign-class        'RuleDesign'
RuleDesignOrdinal-class
                        'RuleDesignOrdinal'
SafetyWindow-class      'SafetyWindow'
SafetyWindowConst-class
                        'SafetyWindowConst'
SafetyWindowSize-class
                        'SafetyWindowSize'
Samples-class           'Samples'
Simulations-class       'Simulations'
SimulationsSummary-class
                        'SimulationsSummary'
Stopping-class          'Stopping'
StoppingAll-class       'StoppingAll'
StoppingAny-class       'StoppingAny'
StoppingCohortsNearDose-class
                        'StoppingCohortsNearDose'
StoppingExternal-class
                        'StoppingExternal'
StoppingHighestDose-class
                        'StoppingHighestDose'
StoppingList-class      'StoppingList'
StoppingLowestDoseHSRBeta-class
                        'StoppingLowestDoseHSRBeta'
StoppingMTDCV-class     'StoppingMTDCV'
StoppingMTDdistribution-class
                        'StoppingMTDdistribution'
StoppingMaxGainCIRatio-class
                        'StoppingMaxGainCIRatio'
StoppingMinCohorts-class
                        'StoppingMinCohorts'
StoppingMinPatients-class
                        'StoppingMinPatients'
StoppingMissingDose-class
                        'StoppingMissingDose'
StoppingOrdinal-class   'StoppingOrdinal'
StoppingPatientsNearDose-class
                        'StoppingPatientsNearDose'
StoppingSpecificDose-class
                        'StoppingSpecificDose'
StoppingTDCIRatio-class
                        'StoppingTDCIRatio'
StoppingTargetBiomarker-class
                        'StoppingTargetBiomarker'
StoppingTargetProb-class
                        'StoppingTargetProb'
TDDesign-class          'TDDesign'
TDsamplesDesign-class   'TDsamplesDesign'
TITELogisticLogNormal-class
                        'TITELogisticLogNormal'
Validate                'Validate'
approximate             Approximate posterior with (log) normal
                        distribution
assertions              Additional Assertions for 'checkmate'
biomarker               Get the Biomarker Levels for a Given
                        Dual-Endpoint Model, Given Dose Levels and
                        Samples
check_equal             Check if All Arguments Are Equal
check_format            Check that an argument is a valid format
                        specification
check_length            Check if vectors are of compatible lengths
check_probabilities     Check if an argument is a probability vector
check_probability       Check if an argument is a single probability
                        value
check_probability_range
                        Check if an argument is a probability range
check_range             Check that an argument is a numerical range
crmPack                 Object-oriented implementation of CRM designs
crmPackExample          Open the Example PDF for crmPack
crmPackHelp             Open the Browser with Help Pages for crmPack
dapply                  Apply a Function to Subsets of Data Frame.
dose                    Computing the Doses for a given independent
                        variable, Model and Samples
doseFunction            Getting the Dose Function for a Given Model
                        Type
dose_grid_range         Getting the Dose Grid Range
efficacy                Computing Expected Efficacy for a Given Dose,
                        Model and Samples
efficacyFunction        Getting the Efficacy Function for a Given Model
                        Type
enable_logging          Verbose Logging
examine                 Obtain Hypothetical Trial Course Table for a
                        Design
fit                     Fit method for the Samples class
fitGain                 Get the fitted 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
fitPEM                  Get the fitted DLT free survival (piecewise
                        exponential model). This function returns a
                        data frame with dose, middle, lower and upper
                        quantiles for the 'PEM' curve. If hazard=TRUE,
gain                    Compute Gain Values based on Pseudo DLE and a
                        Pseudo Efficacy Models and Using Optional
                        Samples.
get,Samples,character-method
                        Get specific parameter samples and produce a
                        data.frame
getEff                  Extracting Efficacy Responses for Subjects
                        Categorized by the DLT
h_all_equivalent        Comparison with Numerical Tolerance and Without
                        Name Comparison
h_blind_plot_data       Helper Function to Blind Plot Data
h_calc_report_label_percentage
                        Helper function to calculate percentage of true
                        stopping rules for report label output
                        calculates true column means and converts
                        output into percentages before combining the
                        output with the report label; output is passed
                        to 'show()' and output with cat to console
h_check_fun_formals     Checking Formals of a Function
h_convert_ordinal_data
                        Convert a Ordinal Data to the Equivalent Binary
                        Data for a Specific Grade
h_convert_ordinal_model
                        Convert an ordinal CRM model to the Equivalent
                        Binary CRM Model for a Specific Grade
h_convert_ordinal_samples
                        Convert a Samples Object from an ordinal Model
                        to the Equivalent Samples Object from a Binary
                        Model
h_default_if_empty      Getting the default value for an empty object
h_find_interval         Find Interval Numbers or Indices and Return
                        Custom Number For 0.
h_format_number         Conditional Formatting Using C-style Formats
h_in_range              Check which elements are in a given range
h_info_theory_dist      Calculating the Information Theoretic Distance
h_is_positive_definite
                        Testing Matrix for Positive Definiteness
h_jags_add_dummy        Appending a Dummy Number for Selected Slots in
                        Data
h_jags_extract_samples
                        Extracting Samples from 'JAGS' 'mcarray' Object
h_jags_get_data         Getting Data for 'JAGS'
h_jags_get_model_inits
                        Setting Initial Values for 'JAGS' Model
                        Parameters
h_jags_join_models      Joining 'JAGS' Models
h_jags_write_model      Writing JAGS Model to a File
h_model_dual_endpoint_beta
                        Update certain components of 'DualEndpoint'
                        model with regard to parameters of the function
                        that models dose-biomarker relationship defined
                        in the 'DualEndpointBeta' class.
h_model_dual_endpoint_rho
                        Update 'DualEndpoint' class model components
                        with regard to DLT and biomarker correlation.
h_model_dual_endpoint_sigma2betaw
                        Update certain components of 'DualEndpoint'
                        model with regard to prior variance factor of
                        the random walk.
h_model_dual_endpoint_sigma2w
                        Update 'DualEndpoint' class model components
                        with regard to biomarker regression variance.
h_next_best_eligible_doses
                        Get Eligible Doses from the Dose Grid.
h_next_best_mg_ci       Credibility Intervals for Max Gain and Target
                        Doses at 'nextBest-NextBestMaxGain' Method.
h_next_best_mg_doses_at_grid
                        Get Closest Grid Doses for a Given Target Doses
                        for 'nextBest-NextBestMaxGain' Method.
h_next_best_mg_plot     Building the Plot for
                        'nextBest-NextBestMaxGain' Method.
h_next_best_mgsamples_plot
                        Building the Plot for
                        'nextBest-NextBestMaxGainSamples' Method.
h_next_best_ncrm_loss_plot
                        Building the Plot for
                        'nextBest-NextBestNCRMLoss' Method.
h_next_best_td_plot     Building the Plot for 'nextBest-NextBestTD'
                        Method.
h_next_best_tdsamples_plot
                        Building the Plot for
                        'nextBest-NextBestTDsamples' Method.
h_null_if_na            Getting 'NULL' for 'NA'
h_obtain_dose_grid_range
                        Helper Function Containing Common Functionality
h_plot_data_cohort_lines
                        Preparing Cohort Lines for Data Plot
h_plot_data_dataordinal
                        Helper Function for the Plot Method of the Data
                        and DataOrdinal Classes
h_plot_data_df          Preparing Data for Plotting
h_rapply                Recursively Apply a Function to a List
h_slots                 Getting the Slots from a S4 Object
h_summarize_add_stats   Helper function to calculate average across
                        iterations for each additional reporting
                        parameter extracts parameter names as specified
                        by user and averaged the values for each
                        specified parameter to 'show()' and output with
                        cat to console
h_test_named_numeric    Check that an argument is a named vector of
                        type numeric
h_unpack_stopit         Helper function to recursively unpack stopping
                        rules and return lists with logical value and
                        label given
h_validate_combine_results
                        Combining S4 Class Validation Results
h_validate_common_data_slots
                        Helper Function performing validation Common to
                        Data and DataOrdinal
knit_print              Render a 'CohortSizeConst' Object
logit                   Shorthand for Logit Function
match_within_tolerance
                        Helper Function for Value Matching with
                        Tolerance
maxDose                 Determine the Maximum Possible Next Dose
maxSize                 "MAX" Combination of Cohort Size Rules
mcmc                    Obtaining Posterior Samples for all Model
                        Parameters
minSize                 "MIN" Combination of Cohort Size Rules
names,Samples-method    The Names of the Sampled Parameters
nextBest                Finding the Next Best Dose
ngrid                   Number of Doses in Grid
or-Stopping-Stopping    Combine Two Stopping Rules with OR
or-Stopping-StoppingAny
                        Combine an Atomic Stopping Rule and a Stopping
                        List with OR
or-StoppingAny-Stopping
                        Combine a Stopping List and an Atomic Stopping
                        Rule with OR
plot,Data,ModelTox-method
                        Plot of the fitted dose-tox based with a given
                        pseudo DLE model and data without samples
plot,DataDA,missing-method
                        Plot Method for the 'DataDA' 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 'DualSimulations'
plot,DualSimulationsSummary,missing-method
                        Plot Dual-Endpoint Design Simulation Summary
plot,GeneralSimulations,missing-method
                        Plot 'GeneralSimulations'
plot,GeneralSimulationsSummary,missing-method
                        Plot 'GeneralSimulationsSummary'
plot,PseudoDualFlexiSimulations,missing-method
                        Plot 'PseudoDualFlexiSimulations'
plot,PseudoDualSimulations,missing-method
                        Plot 'PseudoDualSimulations'
plot,PseudoDualSimulationsSummary,missing-method
                        Plot 'PseudoDualSimulationsSummary'
plot,PseudoSimulationsSummary,missing-method
                        Plot 'PseudoSimulationsSummary'
plot,Samples,DALogisticLogNormal-method
                        Plotting dose-toxicity model fits
plot,Samples,DualEndpoint-method
                        Plotting dose-toxicity and dose-biomarker model
                        fits
plot,Samples,GeneralModel-method
                        Plotting dose-toxicity model fits
plot,Samples,ModelEff-method
                        Plot the fitted dose-efficacy 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 Model-Based Design Simulation Summary
plot.gtable             Plot '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
positive_number         'positive_number'
prob                    Computing Toxicity Probabilities for a Given
                        Dose, Model and Samples
probFunction            Getting the Prob Function for a Given Model
                        Type
probit                  Shorthand for Probit Function
saveSample              Determining if this Sample Should be Saved
set_seed                Helper Function to Set and Save the RNG Seed
show,DualSimulationsSummary-method
                        Show the Summary of Dual-Endpoint Simulations
show,GeneralSimulationsSummary-method
                        Show the Summary of the Simulations
show,PseudoDualSimulationsSummary-method
                        Show the Summary of 'PseudoDualSimulations'
show,PseudoSimulationsSummary-method
                        Show the Summary of 'PseudoSimulations'
show,SimulationsSummary-method
                        Show the Summary of Model-Based Design
                        Simulations
simulate,DADesign-method
                        Simulate outcomes from a time-to-DLT augmented
                        CRM design
simulate,Design-method
                        Simulate outcomes from a CRM design
simulate,DesignGrouped-method
                        Simulate Method for the 'DesignGrouped' Class
simulate,DualDesign-method
                        Simulate outcomes from a dual-endpoint design
simulate,DualResponsesDesign-method
                        Simulate dose escalation procedure using both
                        DLE and efficacy responses without samples
simulate,DualResponsesSamplesDesign-method
                        Simulate dose escalation procedure using DLE
                        and efficacy responses with samples
simulate,RuleDesign-method
                        Simulate outcomes from a rule-based design
simulate,TDDesign-method
                        Simulate dose escalation procedure using DLE
                        responses only without samples
simulate,TDsamplesDesign-method
                        Simulate dose escalation procedure using DLE
                        responses only with DLE samples
size                    Size of an Object
stopTrial               Stop the trial?
summary,DualSimulations-method
                        Summarize Dual-Endpoint Design Simulations
summary,GeneralSimulations-method
                        Summarize the 'GeneralSimulations', Relative to
                        a Given Truth
summary,PseudoDualFlexiSimulations-method
                        Summarize 'PseudoDualFlexiSimulations'
summary,PseudoDualSimulations-method
                        Summarize 'PseudoDualSimulations'
summary,PseudoSimulations-method
                        Summarize 'PseudoSimulations'
summary,Simulations-method
                        Summarize Model-Based Design Simulations
tidy                    Tidying 'CrmPackClass' objects
update,Data-method      Updating 'Data' Objects
update,DataDA-method    Updating 'DataDA' Objects
update,DataDual-method
                        Updating 'DataDual' Objects
update,DataOrdinal-method
                        Updating 'DataOrdinal' Objects
update,DataParts-method
                        Updating 'DataParts' Objects
update,ModelPseudo-method
                        Update method for the 'ModelPseudo' model
                        class. This is a method to update the model
                        class slots (estimates, parameters, variables
                        and etc.), when the new data (e.g. new
                        observations of responses) are available. This
                        method is mostly used to obtain new modal
                        estimates for pseudo model parameters.
v_cohort_size           Internal Helper Functions for Validation of
                        'CohortSize' Objects
v_data_objects          Internal Helper Functions for Validation of
                        'GeneralData' Objects
v_design                Internal Helper Functions for Validation of
                        'RuleDesign' Objects
v_general_simulations   Internal Helper Functions for Validation of
                        'GeneralSimulations' Objects
v_increments            Internal Helper Functions for Validation of
                        'Increments' Objects
v_mcmcoptions_objects   Internal Helper Functions for Validation of
                        'McmcOptions' Objects
v_model_objects         Internal Helper Functions for Validation of
                        'GeneralModel' and 'ModelPseudo' Objects
v_model_params          Internal Helper Functions for Validation of
                        Model Parameters Objects
v_next_best             Internal Helper Functions for Validation of
                        'NextBest' Objects
v_pseudo_simulations    Internal Helper Functions for Validation of
                        'PseudoSimulations' Objects
v_safety_window         Internal Helper Functions for Validation of
                        'SafetyWindow' Objects
v_samples_objects       Internal Helper Functions for Validation of
                        'Samples' Objects
v_stopping              Internal Helper Functions for Validation of
                        'Stopping' Objects
windowLength            Determine the Safety Window Length of the Next
                        Cohort
