# Object-Oriented Implementation of Dose Escalation Designs

## Documentation for package ‘crmPack’ version 2.0.1

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

A B C D E F G H I K L M N O P Q R S T U V W misc

crmPack-package | Object-oriented implementation of CRM designs

## -- A --

and-Stopping-Stopping | Combine Two Stopping Rules with AND
and-Stopping-StoppingAll | Combine an Atomic Stopping Rule and a Stopping List with AND
and-StoppingAll-Stopping | Combine a Stopping List and an Atomic Stopping Rule with AND
approximate | Approximate posterior with (log) normal distribution
approximate-method | Approximate posterior with (log) normal distribution
assertions | Additional Assertions for 'checkmate'
assert_equal | Check if All Arguments Are Equal
assert_format | Check that an argument is a valid format specification
assert_length | Check if vectors are of compatible lengths
assert_probabilities | Check if an argument is a probability vector
assert_probability | Check if an argument is a single probability value
assert_probability_range | Check if an argument is a probability range
assert_range | Check that an argument is a numerical range

## -- B --

biomarker | Get the Biomarker Levels for a Given Dual-Endpoint Model, Given Dose Levels and Samples
biomarker-DualEndpoint | Get the Biomarker Levels for a Given Dual-Endpoint Model, Given Dose Levels and Samples
biomarker-method | Get the Biomarker Levels for a Given Dual-Endpoint Model, Given Dose Levels and Samples

## -- C --

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
CohortSize | 'CohortSize'
CohortSize-class | 'CohortSize'
CohortSizeConst | 'CohortSizeConst'
CohortSizeConst-class | 'CohortSizeConst'
CohortSizeDLT | 'CohortSizeDLT'
CohortSizeDLT-class | 'CohortSizeDLT'
CohortSizeMax | 'CohortSizeMax'
CohortSizeMax-class | 'CohortSizeMax'
CohortSizeMin | 'CohortSizeMin'
CohortSizeMin-class | 'CohortSizeMin'
CohortSizeOrdinal | 'CohortSizeOrdinal'
CohortSizeOrdinal-class | 'CohortSizeOrdinal'
CohortSizeParts | 'CohortSizeParts'
CohortSizeParts-class | 'CohortSizeParts'
CohortSizeRange | 'CohortSizeRange'
CohortSizeRange-class | 'CohortSizeRange'
crmPack | Object-oriented implementation of CRM designs
CrmPackClass | 'CrmPackClass'
CrmPackClass-class | 'CrmPackClass'
crmPackExample | Open the Example PDF for crmPack
crmPackHelp | Open the Browser with Help Pages for crmPack

## -- D --

DADesign | 'DADesign'
DADesign-class | 'DADesign'
DALogisticLogNormal | 'DALogisticLogNormal'
DALogisticLogNormal-class | 'DALogisticLogNormal'
dapply | Apply a Function to Subsets of Data Frame.
DASimulations | 'DASimulations'
DASimulations-class | 'DASimulations'
Data | 'Data'
Data-class | 'Data'
DataDA | 'DataDA'
DataDA-class | 'DataDA'
DataDual | 'DataDual'
DataDual-class | 'DataDual'
DataGrouped | 'DataGrouped'
DataGrouped-class | 'DataGrouped'
DataMixture | 'DataMixture'
DataMixture-class | 'DataMixture'
DataOrdinal | 'DataOrdinal'
DataOrdinal-class | 'DataOrdinal'
DataParts | 'DataParts'
DataParts-class | 'DataParts'
Design | 'Design'
Design-class | 'Design'
DesignGrouped | 'DesignGrouped'
DesignGrouped-class | 'DesignGrouped'
DesignOrdinal | 'DesignOrdinal'
DesignOrdinal-class | 'DesignOrdinal'
disable_logging | Verbose Logging
dose | Computing the Doses for a given independent variable, Model and Samples
dose-DualEndpoint | Computing the Doses for a given independent variable, Model and Samples
dose-EffFlexi | Computing the Doses for a given independent variable, Model and Samples
dose-Effloglog-noSamples | Computing the Doses for a given independent variable, Model and Samples
dose-LogisticIndepBeta | Computing the Doses for a given independent variable, Model and Samples
dose-LogisticIndepBeta-noSamples | Computing the Doses for a given independent variable, Model and Samples
dose-LogisticKadane | Computing the Doses for a given independent variable, Model and Samples
dose-LogisticKadaneBetaGamma | Computing the Doses for a given independent variable, Model and Samples
dose-LogisticLogNormal | Computing the Doses for a given independent variable, Model and Samples
dose-LogisticLogNormalGrouped | Computing the Doses for a given independent variable, Model and Samples
dose-LogisticLogNormalMixture | Computing the Doses for a given independent variable, Model and Samples
dose-LogisticLogNormalOrdinal | Computing the Doses for a given independent variable, Model and Samples
dose-LogisticLogNormalSub | Computing the Doses for a given independent variable, Model and Samples
dose-LogisticNormal | Computing the Doses for a given independent variable, Model and Samples
dose-LogisticNormalFixedMixture | Computing the Doses for a given independent variable, Model and Samples
dose-LogisticNormalMixture | Computing the Doses for a given independent variable, Model and Samples
dose-method | Computing the Doses for a given independent variable, Model and Samples
dose-OneParExpPrior | Computing the Doses for a given independent variable, Model and Samples
dose-OneParLogNormalPrior | Computing the Doses for a given independent variable, Model and Samples
dose-ProbitLogNormal | Computing the Doses for a given independent variable, Model and Samples
dose-ProbitLogNormalRel | Computing the Doses for a given independent variable, Model and Samples
doseFunction | Getting the Dose Function for a Given Model Type
doseFunction-GeneralModel | Getting the Dose Function for a Given Model Type
doseFunction-LogisticLogNormalOrdinal | Getting the Dose Function for a Given Model Type
doseFunction-method | Getting the Dose Function for a Given Model Type
doseFunction-ModelPseudo | Getting the Dose Function for a Given Model Type
dose_grid_range | Getting the Dose Grid Range
dose_grid_range-Data | Getting the Dose Grid Range
dose_grid_range-method | Getting the Dose Grid Range
DualDesign | 'DualDesign'
DualDesign-class | 'DualDesign'
DualEndpoint | 'DualEndpoint'
DualEndpoint-class | 'DualEndpoint'
DualEndpointBeta | 'DualEndpointBeta'
DualEndpointBeta-class | 'DualEndpointBeta'
DualEndpointEmax | 'DualEndpointEmax'
DualEndpointEmax-class | 'DualEndpointEmax'
DualEndpointRW | 'DualEndpointRW'
DualEndpointRW-class | 'DualEndpointRW'
DualResponsesDesign | 'DualResponsesDesign.R'
DualResponsesDesign-class | 'DualResponsesDesign.R'
DualResponsesSamplesDesign | 'DualResponsesSamplesDesign'
DualResponsesSamplesDesign-class | 'DualResponsesSamplesDesign'
DualSimulations | 'DualSimulations'
DualSimulations-class | 'DualSimulations'
DualSimulationsSummary | 'DualSimulationsSummary'
DualSimulationsSummary-class | 'DualSimulationsSummary'

## -- E --

EffFlexi | 'EffFlexi'
EffFlexi-class | 'EffFlexi'
efficacy | Computing Expected Efficacy for a Given Dose, Model and Samples
efficacy-EffFlexi | Computing Expected Efficacy for a Given Dose, Model and Samples
efficacy-Effloglog | Computing Expected Efficacy for a Given Dose, Model and Samples
efficacy-Effloglog-noSamples | Computing Expected Efficacy for a Given Dose, Model and Samples
efficacy-method | Computing Expected Efficacy for a Given Dose, Model and Samples
efficacyFunction | Getting the Efficacy Function for a Given Model Type
efficacyFunction-method | Getting the Efficacy Function for a Given Model Type
efficacyFunction-ModelEff | Getting the Efficacy Function for a Given Model Type
Effloglog | 'Effloglog'
Effloglog-class | 'Effloglog'
enable_logging | Verbose Logging
examine | Obtain Hypothetical Trial Course Table for a Design
examine-method | Obtain Hypothetical Trial Course Table for a Design
expect_format | Check that an argument is a valid format specification
expect_probabilities | Check if an argument is a probability vector
expect_probability | Check if an argument is a single probability value
expect_probability_range | Check if an argument is a probability range
expect_range | Check that an argument is a numerical range

## -- F --

fit | Fit method for the Samples class
fit-method | 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
fitGain-method | 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,
fitPEM-method | 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,
FractionalCRM | 'FractionalCRM'
FractionalCRM-class | 'FractionalCRM'

## -- G --

gain | Compute Gain Values based on Pseudo DLE and a Pseudo Efficacy Models and Using Optional Samples.
gain-method | Compute Gain Values based on Pseudo DLE and a Pseudo Efficacy Models and Using Optional Samples.
gain-ModelTox-Effloglog-noSamples | Compute Gain Values based on Pseudo DLE and a Pseudo Efficacy Models and Using Optional Samples.
gain-ModelTox-ModelEff | Compute Gain Values based on Pseudo DLE and a Pseudo Efficacy Models and Using Optional Samples.
GeneralData | 'GeneralData'
GeneralData-class | 'GeneralData'
GeneralModel | 'GeneralModel'
GeneralModel-class | 'GeneralModel'
GeneralSimulations | 'GeneralSimulations'
GeneralSimulations-class | 'GeneralSimulations'
GeneralSimulationsSummary | 'GeneralSimulationsSummary'
GeneralSimulationsSummary-class | 'GeneralSimulationsSummary'
get-method | Get specific parameter samples and produce a data.frame
getEff | Extracting Efficacy Responses for Subjects Categorized by the DLT
getEff-DataDual | Extracting Efficacy Responses for Subjects Categorized by the DLT
getEff-method | Extracting Efficacy Responses for Subjects Categorized by the DLT

## -- H --

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_doses_unique_per_cohort | Internal Helper Functions for Validation of 'GeneralData' Objects
h_find_interval | Find Interval Numbers or Indices and Return Custom Number For 0.
h_format_number | Conditional Formatting Using C-style Formats
h_info_theory_dist | Calculating the Information Theoretic Distance
h_in_range | Check which elements are in a given range
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_mgsamples_plot | Building the Plot for 'nextBest-NextBestMaxGainSamples' Method.
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_ncrm_loss_plot | Building the Plot for 'nextBest-NextBestNCRMLoss' Method.
h_next_best_tdsamples_plot | Building the Plot for 'nextBest-NextBestTDsamples' Method.
h_next_best_td_plot | Building the Plot for 'nextBest-NextBestTD' 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_plot_data_df-method | 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

## -- I --

Increments | 'Increments'
Increments-class | 'Increments'
IncrementsDoseLevels | 'IncrementsDoseLevels'
IncrementsDoseLevels-class | 'IncrementsDoseLevels'
IncrementsHSRBeta | 'IncrementsHSRBeta'
IncrementsHSRBeta-class | 'IncrementsHSRBeta'
IncrementsMaxToxProb | 'IncrementsMaxToxProb'
IncrementsMaxToxProb-class | 'IncrementsMaxToxProb'
IncrementsMin | 'IncrementsMin'
IncrementsMin-class | 'IncrementsMin'
IncrementsOrdinal | 'IncrementsOrdinal'
IncrementsOrdinal-class | 'IncrementsOrdinal'
IncrementsRelative | 'IncrementsRelative'
IncrementsRelative-class | 'IncrementsRelative'
IncrementsRelativeDLT | 'IncrementsRelativeDLT'
IncrementsRelativeDLT-class | 'IncrementsRelativeDLT'
IncrementsRelativeDLTCurrent | 'IncrementsRelativeDLTCurrent'
IncrementsRelativeDLTCurrent-class | 'IncrementsRelativeDLTCurrent'
IncrementsRelativeParts | 'IncrementsRelativeParts'
IncrementsRelativeParts-class | 'IncrementsRelativeParts'
is_logging_enabled | Verbose Logging

## -- K --

knit_print | Render a 'CohortSizeConst' Object
knit_print.CohortSizeConst | Render a 'CohortSizeConst' Object
knit_print.CohortSizeDLT | Render a 'CohortSizeConst' Object
knit_print.CohortSizeMax | Render a 'CohortSizeConst' Object
knit_print.CohortSizeMin | Render a 'CohortSizeConst' Object
knit_print.CohortSizeOrdinal | Render a 'CohortSizeConst' Object
knit_print.CohortSizeParts | Render a 'CohortSizeConst' Object
knit_print.CohortSizeRange | Render a 'CohortSizeConst' Object
knit_print.DADesign | Render a 'CohortSizeConst' Object
knit_print.DataParts | Render a 'CohortSizeConst' Object
knit_print.Design | Render a 'CohortSizeConst' Object
knit_print.DesignGrouped | Render a 'CohortSizeConst' Object
knit_print.DesignOrdinal | Render a 'CohortSizeConst' Object
knit_print.DualDesign | Render a 'CohortSizeConst' Object
knit_print.DualEndpoint | Render a 'CohortSizeConst' Object
knit_print.DualResponsesDesign | Render a 'CohortSizeConst' Object
knit_print.DualResponsesSamplesDesign | Render a 'CohortSizeConst' Object
knit_print.Effloglog | Render a 'CohortSizeConst' Object
knit_print.GeneralData | Render a 'CohortSizeConst' Object
knit_print.GeneralModel | Render a 'CohortSizeConst' Object
knit_print.IncrementsDoseLevels | Render a 'CohortSizeConst' Object
knit_print.IncrementsHSRBeta | Render a 'CohortSizeConst' Object
knit_print.IncrementsMin | Render a 'CohortSizeConst' Object
knit_print.IncrementsOrdinal | Render a 'CohortSizeConst' Object
knit_print.IncrementsRelative | Render a 'CohortSizeConst' Object
knit_print.IncrementsRelativeDLT | Render a 'CohortSizeConst' Object
knit_print.IncrementsRelativeDLTCurrent | Render a 'CohortSizeConst' Object
knit_print.IncrementsRelativeParts | Render a 'CohortSizeConst' Object
knit_print.LogisticIndepBeta | Render a 'CohortSizeConst' Object
knit_print.LogisticKadane | Render a 'CohortSizeConst' Object
knit_print.LogisticKadaneBetaGamma | Render a 'CohortSizeConst' Object
knit_print.LogisticLogNormal | Render a 'CohortSizeConst' Object
knit_print.LogisticLogNormalGrouped | Render a 'CohortSizeConst' Object
knit_print.LogisticLogNormalMixture | Render a 'CohortSizeConst' Object
knit_print.LogisticLogNormalOrdinal | Render a 'CohortSizeConst' Object
knit_print.LogisticLogNormalSub | Render a 'CohortSizeConst' Object
knit_print.LogisticNormalFixedMixture | Render a 'CohortSizeConst' Object
knit_print.LogisticNormalMixture | Render a 'CohortSizeConst' Object
knit_print.ModelParamsNormal | Render a 'CohortSizeConst' Object
knit_print.NextBestDualEndpoint | Render a 'CohortSizeConst' Object
knit_print.NextBestInfTheory | Render a 'CohortSizeConst' Object
knit_print.NextBestMaxGain | Render a 'CohortSizeConst' Object
knit_print.NextBestMaxGainSamples | Render a 'CohortSizeConst' Object
knit_print.NextBestMinDist | Render a 'CohortSizeConst' Object
knit_print.NextBestMTD | Render a 'CohortSizeConst' Object
knit_print.NextBestNCRM | Render a 'CohortSizeConst' Object
knit_print.NextBestNCRMLoss | Render a 'CohortSizeConst' Object
knit_print.NextBestOrdinal | Render a 'CohortSizeConst' Object
knit_print.NextBestProbMTDLTE | Render a 'CohortSizeConst' Object
knit_print.NextBestProbMTDMinDist | Render a 'CohortSizeConst' Object
knit_print.NextBestTD | Render a 'CohortSizeConst' Object
knit_print.NextBestTDsamples | Render a 'CohortSizeConst' Object
knit_print.NextBestThreePlusThree | Render a 'CohortSizeConst' Object
knit_print.OneParExpPrior | Render a 'CohortSizeConst' Object
knit_print.OneParLogNormalPrior | Render a 'CohortSizeConst' Object
knit_print.RuleDesign | Render a 'CohortSizeConst' Object
knit_print.RuleDesignOrdinal | Render a 'CohortSizeConst' Object
knit_print.SafetyWindow | Render a 'CohortSizeConst' Object
knit_print.SafetyWindowConst | Render a 'CohortSizeConst' Object
knit_print.SafetyWindowSize | Render a 'CohortSizeConst' Object
knit_print.StartingDose | Render a 'CohortSizeConst' Object
knit_print.StoppingAll | Render a 'CohortSizeConst' Object
knit_print.StoppingAny | Render a 'CohortSizeConst' Object
knit_print.StoppingCohortsNearDose | Render a 'CohortSizeConst' Object
knit_print.StoppingHighestDose | Render a 'CohortSizeConst' Object
knit_print.StoppingList | Render a 'CohortSizeConst' Object
knit_print.StoppingLowestDoseHSRBeta | Render a 'CohortSizeConst' Object
knit_print.StoppingMaxGainCIRatio | Render a 'CohortSizeConst' Object
knit_print.StoppingMinCohorts | Render a 'CohortSizeConst' Object
knit_print.StoppingMinPatients | Render a 'CohortSizeConst' Object
knit_print.StoppingMissingDose | Render a 'CohortSizeConst' Object
knit_print.StoppingMTDCV | Render a 'CohortSizeConst' Object
knit_print.StoppingMTDdistribution | Render a 'CohortSizeConst' Object
knit_print.StoppingOrdinal | Render a 'CohortSizeConst' Object
knit_print.StoppingPatientsNearDose | Render a 'CohortSizeConst' Object
knit_print.StoppingSpecificDose | Render a 'CohortSizeConst' Object
knit_print.StoppingTargetBiomarker | Render a 'CohortSizeConst' Object
knit_print.StoppingTargetProb | Render a 'CohortSizeConst' Object
knit_print.StoppingTDCIRatio | Render a 'CohortSizeConst' Object
knit_print.TDDesign | Render a 'CohortSizeConst' Object
knit_print.TDsamplesDesign | Render a 'CohortSizeConst' Object

## -- L --

LogisticIndepBeta | 'LogisticIndepBeta'
LogisticIndepBeta-class | 'LogisticIndepBeta'
LogisticKadane | 'LogisticKadane'
LogisticKadane-class | 'LogisticKadane'
LogisticKadaneBetaGamma | 'LogisticKadaneBetaGamma'
LogisticKadaneBetaGamma-class | 'LogisticKadaneBetaGamma'
LogisticLogNormal | 'LogisticLogNormal'
LogisticLogNormal-class | 'LogisticLogNormal'
LogisticLogNormalGrouped | 'LogisticLogNormalGrouped'
LogisticLogNormalGrouped-class | 'LogisticLogNormalGrouped'
LogisticLogNormalMixture | 'LogisticLogNormalMixture'
LogisticLogNormalMixture-class | 'LogisticLogNormalMixture'
LogisticLogNormalOrdinal | 'LogisticLogNormalOrdinal'
LogisticLogNormalOrdinal-class | 'LogisticLogNormalOrdinal'
LogisticLogNormalSub | 'LogisticLogNormalSub'
LogisticLogNormalSub-class | 'LogisticLogNormalSub'
LogisticNormal | 'LogisticNormal'
LogisticNormal-class | 'LogisticNormal'
LogisticNormalFixedMixture | 'LogisticNormalFixedMixture'
LogisticNormalFixedMixture-class | 'LogisticNormalFixedMixture'
LogisticNormalMixture | 'LogisticNormalMixture'
LogisticNormalMixture-class | 'LogisticNormalMixture'
logit | Shorthand for Logit Function
log_trace | Verbose Logging

## -- M --

match_within_tolerance | Helper Function for Value Matching with Tolerance
maxDose | Determine the Maximum Possible Next Dose
maxDose-IncrementsDoseLevels | Determine the Maximum Possible Next Dose
maxDose-IncrementsHSRBeta | Determine the Maximum Possible Next Dose
maxDose-IncrementsMaxToxProb | Determine the Maximum Possible Next Dose
maxDose-IncrementsMin | Determine the Maximum Possible Next Dose
maxDose-IncrementsOrdinal | Determine the Maximum Possible Next Dose
maxDose-IncrementsRelative | Determine the Maximum Possible Next Dose
maxDose-IncrementsRelativeDLT | Determine the Maximum Possible Next Dose
maxDose-IncrementsRelativeDLTCurrent | Determine the Maximum Possible Next Dose
maxDose-IncrementsRelativeParts | Determine the Maximum Possible Next Dose
maxDose-method | Determine the Maximum Possible Next Dose
maxSize | "MAX" Combination of Cohort Size Rules
maxSize-CohortSize | "MAX" Combination of Cohort Size Rules
maxSize-method | "MAX" Combination of Cohort Size Rules
mcmc | Obtaining Posterior Samples for all Model Parameters
mcmc-Data-LogisticIndepBeta | Obtaining Posterior Samples for all Model Parameters
mcmc-DataDual-EffFlexi | Obtaining Posterior Samples for all Model Parameters
mcmc-DataDual-Effloglog | Obtaining Posterior Samples for all Model Parameters
mcmc-DataMixture | Obtaining Posterior Samples for all Model Parameters
mcmc-DataOrdinal-LogisticLogNormalOrdinal | Obtaining Posterior Samples for all Model Parameters
mcmc-GeneralData | Obtaining Posterior Samples for all Model Parameters
mcmc-GeneralData-DualEndpointBeta | Obtaining Posterior Samples for all Model Parameters
mcmc-GeneralData-DualEndpointEmax | Obtaining Posterior Samples for all Model Parameters
mcmc-GeneralData-DualEndpointRW | Obtaining Posterior Samples for all Model Parameters
mcmc-GeneralData-OneParExpPrior | Obtaining Posterior Samples for all Model Parameters
mcmc-GeneralData-OneParLogNormalPrior | Obtaining Posterior Samples for all Model Parameters
mcmc-method | Obtaining Posterior Samples for all Model Parameters
McmcOptions | 'McmcOptions'
McmcOptions-class | 'McmcOptions'
MinimalInformative | Construct a Minimally Informative Prior
minSize | "MIN" Combination of Cohort Size Rules
minSize-CohortSize | "MIN" Combination of Cohort Size Rules
minSize-method | "MIN" Combination of Cohort Size Rules
ModelEff | 'ModelEff'
ModelEff-class | 'ModelEff'
ModelLogNormal | 'ModelLogNormal'
ModelLogNormal-class | 'ModelLogNormal'
ModelParamsNormal | 'ModelParamsNormal'
ModelParamsNormal-class | 'ModelParamsNormal'
ModelPseudo | 'ModelPseudo'
ModelPseudo-class | 'ModelPseudo'
ModelTox | 'ModelTox'
ModelTox-class | 'ModelTox'

## -- N --

names-method | The Names of the Sampled Parameters
names-Samples | The Names of the Sampled Parameters
NextBest | 'NextBest'
nextBest | Finding the Next Best Dose
NextBest-class | 'NextBest'
nextBest-method | Finding the Next Best Dose
nextBest-NextBestDualEndpoint | Finding the Next Best Dose
nextBest-NextBestEWOC | Finding the Next Best Dose
nextBest-NextBestInfTheory | Finding the Next Best Dose
nextBest-NextBestMaxGain | Finding the Next Best Dose
nextBest-NextBestMaxGainSamples | Finding the Next Best Dose
nextBest-NextBestMinDist | Finding the Next Best Dose
nextBest-NextBestMTD | Finding the Next Best Dose
nextBest-NextBestNCRM | Finding the Next Best Dose
nextBest-NextBestNCRM-DataParts | Finding the Next Best Dose
nextBest-NextBestNCRMLoss | Finding the Next Best Dose
nextBest-NextBestOrdinal | Finding the Next Best Dose
nextBest-NextBestProbMTDLTE | Finding the Next Best Dose
nextBest-NextBestProbMTDMinDist | Finding the Next Best Dose
nextBest-NextBestTD | Finding the Next Best Dose
nextBest-NextBestTDsamples | Finding the Next Best Dose
nextBest-NextBestThreePlusThree | Finding the Next Best Dose
NextBestDualEndpoint | 'NextBestDualEndpoint'
NextBestDualEndpoint-class | 'NextBestDualEndpoint'
NextBestEWOC | 'NextBestEWOC'
NextBestEWOC-class | 'NextBestEWOC'
NextBestInfTheory | 'NextBestInfTheory'
NextBestInfTheory-class | 'NextBestInfTheory'
NextBestMaxGain | 'NextBestMaxGain'
NextBestMaxGain-class | 'NextBestMaxGain'
NextBestMaxGainSamples | 'NextBestMaxGainSamples'
NextBestMaxGainSamples-class | 'NextBestMaxGainSamples'
NextBestMinDist | 'NextBestMinDist'
NextBestMinDist-class | 'NextBestMinDist'
NextBestMTD | 'NextBestMTD'
NextBestMTD-class | 'NextBestMTD'
NextBestNCRM | 'NextBestNCRM'
NextBestNCRM-class | 'NextBestNCRM'
NextBestNCRMLoss | 'NextBestNCRMLoss'
NextBestNCRMLoss-class | 'NextBestNCRMLoss'
NextBestOrdinal | 'NextBestOrdinal'
NextBestOrdinal-class | 'NextBestOrdinal'
NextBestProbMTDLTE | 'NextBestProbMTDLTE'
NextBestProbMTDLTE-class | 'NextBestProbMTDLTE'
NextBestProbMTDMinDist | 'NextBestProbMTDMinDist'
NextBestProbMTDMinDist-class | 'NextBestProbMTDMinDist'
NextBestTD | 'NextBestTD'
NextBestTD-class | 'NextBestTD'
NextBestTDsamples | 'NextBestTDsamples'
NextBestTDsamples-class | 'NextBestTDsamples'
NextBestThreePlusThree | 'NextBestThreePlusThree'
NextBestThreePlusThree-class | 'NextBestThreePlusThree'
ngrid | Number of Doses in Grid
ngrid-Data | Number of Doses in Grid
ngrid-method | Number of Doses in Grid

## -- O --

OneParExpPrior | 'OneParExpPrior'
OneParExpPrior-class | 'OneParExpPrior'
OneParLogNormalPrior | 'OneParLogNormalPrior'
OneParLogNormalPrior-class | 'OneParLogNormalPrior'
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

## -- P --

plot-Data | Helper Function for the Plot Method of the Data and DataOrdinal Classes
plot-DataDA | Plot Method for the 'DataDA' Class
plot-DataDual | Plot Method for the 'DataDual' Class
plot-DualSimulations-missing | Plot 'DualSimulations'
plot-DualSimulationsSummary-missing | Plot Dual-Endpoint Design Simulation Summary
plot-GeneralSimulations-missing | Plot 'GeneralSimulations'
plot-GeneralSimulationsSummary-missing | Plot 'GeneralSimulationsSummary'
plot-method | Plot of the fitted dose-tox based with a given pseudo DLE model and data without samples
plot-method | Helper Function for the Plot Method of the Data and DataOrdinal Classes
plot-method | Plot Method for the 'DataDA' Class
plot-method | Plot of the fitted dose-efficacy based with a given pseudo efficacy model and data without samples
plot-method | Plot Method for the 'DataDual' Class
plot-method | Plot 'DualSimulations'
plot-method | Plot Dual-Endpoint Design Simulation Summary
plot-method | Plot 'GeneralSimulations'
plot-method | Plot 'GeneralSimulationsSummary'
plot-method | Plot 'PseudoDualFlexiSimulations'
plot-method | Plot 'PseudoDualSimulations'
plot-method | Plot 'PseudoDualSimulationsSummary'
plot-method | Plot 'PseudoSimulationsSummary'
plot-method | Plotting dose-toxicity model fits
plot-method | Plotting dose-toxicity and dose-biomarker model fits
plot-method | Plotting dose-toxicity model fits
plot-method | Plot the fitted dose-efficacy curve using a model from 'ModelEff' class with samples
plot-method | Plot the fitted dose-DLE curve using a 'ModelTox' class model with samples
plot-method | Plot Model-Based Design Simulation Summary
plot-PseudoDualFlexiSimulations-missing | Plot 'PseudoDualFlexiSimulations'
plot-PseudoDualSimulations-missing | Plot 'PseudoDualSimulations'
plot-PseudoDualSimulationsSummary-missing | Plot 'PseudoDualSimulationsSummary'
plot-PseudoSimulationsSummary-missing | Plot 'PseudoSimulationsSummary'
plot-SimulationsSummary-missing | 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
plotDualResponses-method | 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
plotGain-method | 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'
print.gtable | Plot 'gtable' Objects
prob | Computing Toxicity Probabilities for a Given Dose, Model and Samples
prob-DualEndpoint | Computing Toxicity Probabilities for a Given Dose, Model and Samples
prob-LogisticIndepBeta | Computing Toxicity Probabilities for a Given Dose, Model and Samples
prob-LogisticIndepBeta-noSamples | Computing Toxicity Probabilities for a Given Dose, Model and Samples
prob-LogisticKadane | Computing Toxicity Probabilities for a Given Dose, Model and Samples
prob-LogisticKadaneBetaGamma | Computing Toxicity Probabilities for a Given Dose, Model and Samples
prob-LogisticLogNormal | Computing Toxicity Probabilities for a Given Dose, Model and Samples
prob-LogisticLogNormalGrouped | Computing Toxicity Probabilities for a Given Dose, Model and Samples
prob-LogisticLogNormalMixture | Computing Toxicity Probabilities for a Given Dose, Model and Samples
prob-LogisticLogNormalOrdinal | Computing Toxicity Probabilities for a Given Dose, Model and Samples
prob-LogisticLogNormalSub | Computing Toxicity Probabilities for a Given Dose, Model and Samples
prob-LogisticNormal | Computing Toxicity Probabilities for a Given Dose, Model and Samples
prob-LogisticNormalFixedMixture | Computing Toxicity Probabilities for a Given Dose, Model and Samples
prob-LogisticNormalMixture | Computing Toxicity Probabilities for a Given Dose, Model and Samples
prob-method | Computing Toxicity Probabilities for a Given Dose, Model and Samples
prob-OneParExpPrior | Computing Toxicity Probabilities for a Given Dose, Model and Samples
prob-OneParLogNormalPrior | Computing Toxicity Probabilities for a Given Dose, Model and Samples
prob-ProbitLogNormal | Computing Toxicity Probabilities for a Given Dose, Model and Samples
prob-ProbitLogNormalRel | Computing Toxicity Probabilities for a Given Dose, Model and Samples
probFunction | Getting the Prob Function for a Given Model Type
probFunction-GeneralModel | Getting the Prob Function for a Given Model Type
probFunction-LogisticLogNormalOrdinal | Getting the Prob Function for a Given Model Type
probFunction-method | Getting the Prob Function for a Given Model Type
probFunction-ModelTox | Getting the Prob Function for a Given Model Type
probit | Shorthand for Probit Function
ProbitLogNormal | 'ProbitLogNormal'
ProbitLogNormal-class | 'ProbitLogNormal'
ProbitLogNormalLogDose | 'ProbitLogNormal'
ProbitLogNormalRel | 'ProbitLogNormalRel'
ProbitLogNormalRel-class | 'ProbitLogNormalRel'
PseudoDualFlexiSimulations | 'PseudoDualFlexiSimulations'
PseudoDualFlexiSimulations-class | 'PseudoDualFlexiSimulations'
PseudoDualSimulations | 'PseudoDualSimulations'
PseudoDualSimulations-class | 'PseudoDualSimulations'
PseudoDualSimulationsSummary | 'PseudoDualSimulationsSummary'
PseudoDualSimulationsSummary-class | 'PseudoDualSimulationsSummary'
PseudoSimulations | 'PseudoSimulations'
PseudoSimulations-class | 'PseudoSimulations'
PseudoSimulationsSummary | 'PseudoSimulationsSummary'
PseudoSimulationsSummary-class | 'PseudoSimulationsSummary'

## -- Q --

Quantiles2LogisticNormal | Convert Prior Quantiles to Logistic (Log) Normal Model

## -- R --

RuleDesign | 'RuleDesign'
RuleDesign-class | 'RuleDesign'
RuleDesignOrdinal | 'RuleDesignOrdinal'
RuleDesignOrdinal-class | 'RuleDesignOrdinal'

## -- S --

SafetyWindow | 'SafetyWindow'
SafetyWindow-class | 'SafetyWindow'
SafetyWindowConst | 'SafetyWindowConst'
SafetyWindowConst-class | 'SafetyWindowConst'
SafetyWindowSize | 'SafetyWindowSize'
SafetyWindowSize-class | 'SafetyWindowSize'
Samples | 'Samples'
Samples-class | 'Samples'
saveSample | Determining if this Sample Should be Saved
saveSample-McmcOptions | Determining if this Sample Should be Saved
saveSample-method | Determining if this Sample Should be Saved
set_seed | Helper Function to Set and Save the RNG Seed
show-DualSimulationsSummary | Show the Summary of Dual-Endpoint Simulations
show-GeneralSimulationsSummary | Show the Summary of the Simulations
show-method | Show the Summary of Dual-Endpoint Simulations
show-method | Show the Summary of the Simulations
show-method | Show the Summary of 'PseudoDualSimulations'
show-method | Show the Summary of 'PseudoSimulations'
show-method | Show the Summary of Model-Based Design Simulations
show-PseudoDualSimulationsSummary | Show the Summary of 'PseudoDualSimulations'
show-PseudoSimulationsSummary | Show the Summary of 'PseudoSimulations'
show-SimulationsSummary | Show the Summary of Model-Based Design Simulations
simulate-DesignGrouped | Simulate Method for the 'DesignGrouped' Class
simulate-method | Simulate outcomes from a time-to-DLT augmented CRM design
simulate-method | Simulate outcomes from a CRM design
simulate-method | Simulate Method for the 'DesignGrouped' Class
simulate-method | Simulate outcomes from a dual-endpoint design
simulate-method | Simulate dose escalation procedure using both DLE and efficacy responses without samples
simulate-method | Simulate dose escalation procedure using DLE and efficacy responses with samples
simulate-method | Simulate outcomes from a rule-based design
simulate-method | Simulate dose escalation procedure using DLE responses only without samples
simulate-method | Simulate dose escalation procedure using DLE responses only with DLE samples
Simulations | 'Simulations'
Simulations-class | 'Simulations'
SimulationsSummary | 'SimulationsSummary'
SimulationsSummary-class | 'SimulationsSummary'
size | Size of an Object
size-CohortSizeConst | Size of an Object
size-CohortSizeDLT | Size of an Object
size-CohortSizeMax | Size of an Object
size-CohortSizeMin | Size of an Object
size-CohortSizeOrdinal | Size of an Object
size-CohortSizeParts | Size of an Object
size-CohortSizeRange | Size of an Object
size-McmcOptions | Size of an Object
size-method | Size of an Object
size-Samples | Size of an Object
Stopping | 'Stopping'
Stopping-class | 'Stopping'
StoppingAll | 'StoppingAll'
StoppingAll-class | 'StoppingAll'
StoppingAny | 'StoppingAny'
StoppingAny-class | 'StoppingAny'
StoppingCohortsNearDose | 'StoppingCohortsNearDose'
StoppingCohortsNearDose-class | 'StoppingCohortsNearDose'
StoppingExternal | 'StoppingExternal'
StoppingExternal-class | 'StoppingExternal'
StoppingHighestDose | 'StoppingHighestDose'
StoppingHighestDose-class | 'StoppingHighestDose'
StoppingList | 'StoppingList'
StoppingList-class | 'StoppingList'
StoppingLowestDoseHSRBeta | 'StoppingLowestDoseHSRBeta'
StoppingLowestDoseHSRBeta-class | 'StoppingLowestDoseHSRBeta'
StoppingMaxGainCIRatio | 'StoppingMaxGainCIRatio'
StoppingMaxGainCIRatio-class | 'StoppingMaxGainCIRatio'
StoppingMinCohorts | 'StoppingMinCohorts'
StoppingMinCohorts-class | 'StoppingMinCohorts'
StoppingMinPatients | 'StoppingMinPatients'
StoppingMinPatients-class | 'StoppingMinPatients'
StoppingMissingDose | 'StoppingMissingDose'
StoppingMissingDose-class | 'StoppingMissingDose'
StoppingMTDCV | 'StoppingMTDCV'
StoppingMTDCV-class | 'StoppingMTDCV'
StoppingMTDdistribution | 'StoppingMTDdistribution'
StoppingMTDdistribution-class | 'StoppingMTDdistribution'
StoppingOrdinal | 'StoppingOrdinal'
StoppingOrdinal-class | 'StoppingOrdinal'
StoppingPatientsNearDose | 'StoppingPatientsNearDose'
StoppingPatientsNearDose-class | 'StoppingPatientsNearDose'
StoppingSpecificDose | 'StoppingSpecificDose'
StoppingSpecificDose-class | 'StoppingSpecificDose'
StoppingTargetBiomarker | 'StoppingTargetBiomarker'
StoppingTargetBiomarker-class | 'StoppingTargetBiomarker'
StoppingTargetProb | 'StoppingTargetProb'
StoppingTargetProb-class | 'StoppingTargetProb'
StoppingTDCIRatio | 'StoppingTDCIRatio'
StoppingTDCIRatio-class | 'StoppingTDCIRatio'
stopTrial | Stop the trial?
stopTrial-method | Stop the trial?
stopTrial-StoppingAll | Stop the trial?
stopTrial-StoppingAny | Stop the trial?
stopTrial-StoppingCohortsNearDose | Stop the trial?
stopTrial-StoppingExternal | Stop the trial?
stopTrial-StoppingHighestDose | Stop the trial?
stopTrial-StoppingList | Stop the trial?
stopTrial-StoppingLowestDoseHSRBeta | Stop the trial?
stopTrial-StoppingMaxGainCIRatio | Stop the trial?
stopTrial-StoppingMinCohorts | Stop the trial?
stopTrial-StoppingMinPatients | Stop the trial?
stopTrial-StoppingMissingDose | Stop the trial?
stopTrial-StoppingMTDCV | Stop the trial?
stopTrial-StoppingMTDdistribution | Stop the trial?
stopTrial-StoppingOrdinal | Stop the trial?
stopTrial-StoppingPatientsNearDose | Stop the trial?
stopTrial-StoppingSpecificDose | Stop the trial?
stopTrial-StoppingTargetBiomarker | Stop the trial?
stopTrial-StoppingTargetProb | Stop the trial?
stopTrial-StoppingTDCIRatio | Stop the trial?
summary-DualSimulations | Summarize Dual-Endpoint Design Simulations
summary-GeneralSimulations | Summarize the 'GeneralSimulations', Relative to a Given Truth
summary-method | Summarize Dual-Endpoint Design Simulations
summary-method | Summarize the 'GeneralSimulations', Relative to a Given Truth
summary-method | Summarize 'PseudoDualFlexiSimulations'
summary-method | Summarize 'PseudoDualSimulations'
summary-method | Summarize 'PseudoSimulations'
summary-method | Summarize Model-Based Design Simulations
summary-PseudoDualFlexiSimulations | Summarize 'PseudoDualFlexiSimulations'
summary-PseudoDualSimulations | Summarize 'PseudoDualSimulations'
summary-PseudoSimulations | Summarize 'PseudoSimulations'
summary-Simulations | Summarize Model-Based Design Simulations

## -- T --

TDDesign | 'TDDesign'
TDDesign-class | 'TDDesign'
TDsamplesDesign | 'TDsamplesDesign'
TDsamplesDesign-class | 'TDsamplesDesign'
test_format | Check that an argument is a valid format specification
test_length | Check if vectors are of compatible lengths
test_probabilities | Check if an argument is a probability vector
test_probability | Check if an argument is a single probability value
test_probability_range | Check if an argument is a probability range
test_range | Check that an argument is a numerical range
ThreePlusThreeDesign | 'RuleDesign'
tidy | Tidying 'CrmPackClass' objects
tidy-CohortSizeDLT | Tidying 'CrmPackClass' objects
tidy-CohortSizeMax | Tidying 'CrmPackClass' objects
tidy-CohortSizeMin | Tidying 'CrmPackClass' objects
tidy-CohortSizeParts | Tidying 'CrmPackClass' objects
tidy-CohortSizeRange | Tidying 'CrmPackClass' objects
tidy-CrmPackClass | Tidying 'CrmPackClass' objects
tidy-DataDA | Tidying 'CrmPackClass' objects
tidy-DataDual | Tidying 'CrmPackClass' objects
tidy-DataGrouped | Tidying 'CrmPackClass' objects
tidy-DataMixture | Tidying 'CrmPackClass' objects
tidy-DataOrdinal | Tidying 'CrmPackClass' objects
tidy-DataParts | Tidying 'CrmPackClass' objects
tidy-DualDesign | Tidying 'CrmPackClass' objects
tidy-Effloglog | Tidying 'CrmPackClass' objects
tidy-GeneralData | Tidying 'CrmPackClass' objects
tidy-IncrementsMaxToxProb | Tidying 'CrmPackClass' objects
tidy-IncrementsMin | Tidying 'CrmPackClass' objects
tidy-IncrementsRelative | Tidying 'CrmPackClass' objects
tidy-IncrementsRelativeDLT | Tidying 'CrmPackClass' objects
tidy-IncrementsRelativeParts | Tidying 'CrmPackClass' objects
tidy-LogisticIndepBeta | Tidying 'CrmPackClass' objects
tidy-method | Tidying 'CrmPackClass' objects
tidy-NextBestNCRM | Tidying 'CrmPackClass' objects
tidy-NextBestNCRMLoss | Tidying 'CrmPackClass' objects
tidy-Samples | Tidying 'CrmPackClass' objects
tidy-Simulations | Tidying 'CrmPackClass' objects
TITELogisticLogNormal | 'TITELogisticLogNormal'
TITELogisticLogNormal-class | 'TITELogisticLogNormal'

## -- U --

update-Data | Updating 'Data' Objects
update-DataDA | Updating 'DataDA' Objects
update-DataDual | Updating 'DataDual' Objects
update-DataOrdinal | Updating 'DataOrdinal' Objects
update-DataParts | Updating 'DataParts' Objects
update-method | Updating 'Data' Objects
update-method | Updating 'DataDA' Objects
update-method | Updating 'DataDual' Objects
update-method | Updating 'DataOrdinal' Objects
update-method | Updating 'DataParts' Objects
update-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.
update-ModelPseudo | 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 --

Validate | 'Validate'
v_cohort_size | Internal Helper Functions for Validation of 'CohortSize' Objects
v_cohort_size_const | Internal Helper Functions for Validation of 'CohortSize' Objects
v_cohort_size_dlt | Internal Helper Functions for Validation of 'CohortSize' Objects
v_cohort_size_max | Internal Helper Functions for Validation of 'CohortSize' Objects
v_cohort_size_ordinal | Internal Helper Functions for Validation of 'Increments' Objects
v_cohort_size_parts | Internal Helper Functions for Validation of 'CohortSize' Objects
v_cohort_size_range | Internal Helper Functions for Validation of 'CohortSize' Objects
v_data | Internal Helper Functions for Validation of 'GeneralData' Objects
v_data_da | Internal Helper Functions for Validation of 'GeneralData' Objects
v_data_dual | Internal Helper Functions for Validation of 'GeneralData' Objects
v_data_grouped | Internal Helper Functions for Validation of 'GeneralData' Objects
v_data_mixture | Internal Helper Functions for Validation of 'GeneralData' Objects
v_data_objects | Internal Helper Functions for Validation of 'GeneralData' Objects
v_data_ordinal | Internal Helper Functions for Validation of 'GeneralData' Objects
v_data_parts | Internal Helper Functions for Validation of 'GeneralData' Objects
v_da_simulations | Internal Helper Functions for Validation of 'GeneralSimulations' Objects
v_design | Internal Helper Functions for Validation of 'RuleDesign' Objects
v_design_grouped | Internal Helper Functions for Validation of 'RuleDesign' Objects
v_dual_simulations | Internal Helper Functions for Validation of 'GeneralSimulations' Objects
v_general_data | Internal Helper Functions for Validation of 'GeneralData' Objects
v_general_model | Internal Helper Functions for Validation of 'GeneralModel' and 'ModelPseudo' Objects
v_general_simulations | Internal Helper Functions for Validation of 'GeneralSimulations' Objects
v_increments | Internal Helper Functions for Validation of 'Increments' Objects
v_increments_dose_levels | Internal Helper Functions for Validation of 'Increments' Objects
v_increments_hsr_beta | Internal Helper Functions for Validation of 'Increments' Objects
v_increments_maxtoxprob | Internal Helper Functions for Validation of 'Increments' Objects
v_increments_min | Internal Helper Functions for Validation of 'Increments' Objects
v_increments_ordinal | Internal Helper Functions for Validation of 'Increments' Objects
v_increments_relative | Internal Helper Functions for Validation of 'Increments' Objects
v_increments_relative_dlt | Internal Helper Functions for Validation of 'Increments' Objects
v_increments_relative_parts | Internal Helper Functions for Validation of 'Increments' Objects
v_logisticlognormalordinal | Internal Helper Functions for Validation of 'GeneralModel' and 'ModelPseudo' Objects
v_mcmcoptions_objects | Internal Helper Functions for Validation of 'McmcOptions' Objects
v_mcmc_options | Internal Helper Functions for Validation of 'McmcOptions' Objects
v_model_da_logistic_log_normal | Internal Helper Functions for Validation of 'GeneralModel' and 'ModelPseudo' Objects
v_model_dual_endpoint | Internal Helper Functions for Validation of 'GeneralModel' and 'ModelPseudo' Objects
v_model_dual_endpoint_beta | Internal Helper Functions for Validation of 'GeneralModel' and 'ModelPseudo' Objects
v_model_dual_endpoint_emax | Internal Helper Functions for Validation of 'GeneralModel' and 'ModelPseudo' Objects
v_model_dual_endpoint_rw | Internal Helper Functions for Validation of 'GeneralModel' and 'ModelPseudo' Objects
v_model_eff_flexi | Internal Helper Functions for Validation of 'GeneralModel' and 'ModelPseudo' Objects
v_model_eff_log_log | Internal Helper Functions for Validation of 'GeneralModel' and 'ModelPseudo' Objects
v_model_logistic_indep_beta | Internal Helper Functions for Validation of 'GeneralModel' and 'ModelPseudo' Objects
v_model_logistic_kadane | Internal Helper Functions for Validation of 'GeneralModel' and 'ModelPseudo' Objects
v_model_logistic_kadane_beta_gamma | Internal Helper Functions for Validation of 'GeneralModel' and 'ModelPseudo' Objects
v_model_logistic_log_normal_mix | Internal Helper Functions for Validation of 'GeneralModel' and 'ModelPseudo' Objects
v_model_logistic_normal_fixed_mix | Internal Helper Functions for Validation of 'GeneralModel' and 'ModelPseudo' Objects
v_model_logistic_normal_mix | Internal Helper Functions for Validation of 'GeneralModel' and 'ModelPseudo' Objects
v_model_objects | Internal Helper Functions for Validation of 'GeneralModel' and 'ModelPseudo' Objects
v_model_one_par_exp_normal_prior | Internal Helper Functions for Validation of 'GeneralModel' and 'ModelPseudo' Objects
v_model_one_par_exp_prior | Internal Helper Functions for Validation of 'GeneralModel' and 'ModelPseudo' Objects
v_model_params | Internal Helper Functions for Validation of Model Parameters Objects
v_model_params_normal | Internal Helper Functions for Validation of Model Parameters Objects
v_model_tite_logistic_log_normal | Internal Helper Functions for Validation of 'GeneralModel' and 'ModelPseudo' Objects
v_next_best | Internal Helper Functions for Validation of 'NextBest' Objects
v_next_best_dual_endpoint | Internal Helper Functions for Validation of 'NextBest' Objects
v_next_best_ewoc | Internal Helper Functions for Validation of 'NextBest' Objects
v_next_best_inf_theory | Internal Helper Functions for Validation of 'NextBest' Objects
v_next_best_max_gain_samples | Internal Helper Functions for Validation of 'NextBest' Objects
v_next_best_min_dist | Internal Helper Functions for Validation of 'NextBest' Objects
v_next_best_mtd | Internal Helper Functions for Validation of 'NextBest' Objects
v_next_best_ncrm | Internal Helper Functions for Validation of 'NextBest' Objects
v_next_best_ncrm_loss | Internal Helper Functions for Validation of 'NextBest' Objects
v_next_best_ordinal | Internal Helper Functions for Validation of 'NextBest' Objects
v_next_best_prob_mtd_lte | Internal Helper Functions for Validation of 'NextBest' Objects
v_next_best_prob_mtd_min_dist | Internal Helper Functions for Validation of 'NextBest' Objects
v_next_best_td | Internal Helper Functions for Validation of 'NextBest' Objects
v_next_best_td_samples | Internal Helper Functions for Validation of 'NextBest' Objects
v_pseudo_dual_flex_simulations | Internal Helper Functions for Validation of 'PseudoSimulations' Objects
v_pseudo_dual_simulations | Internal Helper Functions for Validation of 'PseudoSimulations' Objects
v_pseudo_simulations | Internal Helper Functions for Validation of 'PseudoSimulations' Objects
v_rule_design | Internal Helper Functions for Validation of 'RuleDesign' Objects
v_rule_design_ordinal | Internal Helper Functions for Validation of 'RuleDesign' Objects
v_safety_window | Internal Helper Functions for Validation of 'SafetyWindow' Objects
v_safety_window_const | Internal Helper Functions for Validation of 'SafetyWindow' Objects
v_safety_window_size | Internal Helper Functions for Validation of 'SafetyWindow' Objects
v_samples | Internal Helper Functions for Validation of 'Samples' Objects
v_samples_objects | Internal Helper Functions for Validation of 'Samples' Objects
v_simulations | Internal Helper Functions for Validation of 'GeneralSimulations' Objects
v_stopping | Internal Helper Functions for Validation of 'Stopping' Objects
v_stopping_all | Internal Helper Functions for Validation of 'Stopping' Objects
v_stopping_cohorts_near_dose | Internal Helper Functions for Validation of 'Stopping' Objects
v_stopping_list | Internal Helper Functions for Validation of 'Stopping' Objects
v_stopping_min_cohorts | Internal Helper Functions for Validation of 'Stopping' Objects
v_stopping_min_patients | Internal Helper Functions for Validation of 'Stopping' Objects
v_stopping_mtd_cv | Internal Helper Functions for Validation of 'Stopping' Objects
v_stopping_mtd_distribution | Internal Helper Functions for Validation of 'Stopping' Objects
v_stopping_patients_near_dose | Internal Helper Functions for Validation of 'Stopping' Objects
v_stopping_target_biomarker | Internal Helper Functions for Validation of 'Stopping' Objects
v_stopping_target_prob | Internal Helper Functions for Validation of 'Stopping' Objects
v_stopping_tdci_ratio | Internal Helper Functions for Validation of 'Stopping' Objects

## -- W --

windowLength | Determine the Safety Window Length of the Next Cohort
windowLength-method | Determine the Safety Window Length of the Next Cohort
windowLength-SafetyWindowConst | Determine the Safety Window Length of the Next Cohort
windowLength-SafetyWindowSize | Determine the Safety Window Length of the Next Cohort

## -- misc --

&-method | Combine Two Stopping Rules with AND
&-method | Combine an Atomic Stopping Rule and a Stopping List with AND
&-method | Combine a Stopping List and an Atomic Stopping Rule with AND
.CohortSizeConst | 'CohortSizeConst'
.CohortSizeDLT | 'CohortSizeDLT'
.CohortSizeMax | 'CohortSizeMax'
.CohortSizeMin | 'CohortSizeMin'
.CohortSizeOrdinal | 'CohortSizeOrdinal'
.CohortSizeParts | 'CohortSizeParts'
.CohortSizeRange | 'CohortSizeRange'
.CrmPackClass | 'CrmPackClass'
.DADesign | 'DADesign'
.DALogisticLogNormal | 'DALogisticLogNormal'
.DASimulations | 'DASimulations'
.Data | 'Data'
.DataDA | 'DataDA'
.DataDual | 'DataDual'
.DataGrouped | 'DataGrouped'
.DataMixture | 'DataMixture'
.DataOrdinal | 'DataOrdinal'
.DataParts | 'DataParts'
.DefaultCohortSize | 'CohortSize'
.DefaultCohortSizeConst | 'CohortSizeConst'
.DefaultCohortSizeDLT | 'CohortSizeDLT'
.DefaultCohortSizeMax | 'CohortSizeMax'
.DefaultCohortSizeMin | 'CohortSizeMin'
.DefaultCohortSizeOrdinal | 'CohortSizeOrdinal'
.DefaultCohortSizeParts | 'CohortSizeParts'
.DefaultCohortSizeRange | 'CohortSizeRange'
.DefaultDADesign | 'DADesign'
.DefaultDALogisticLogNormal | 'DALogisticLogNormal'
.DefaultDASimulations | 'DASimulations'
.DefaultData | 'Data'
.DefaultDataDA | 'DataDA'
.DefaultDataDual | 'DataDual'
.DefaultDataGeneral | 'GeneralData'
.DefaultDataGrouped | 'DataGrouped'
.DefaultDataMixture | 'DataMixture'
.DefaultDataOrdinal | 'DataOrdinal'
.DefaultDataParts | 'DataParts'
.DefaultDesign | 'Design'
.DefaultDesignGrouped | 'DesignGrouped'
.DefaultDesignOrdinal | 'DesignOrdinal'
.DefaultDualDesign | 'DualDesign'
.DefaultDualEndpoint | 'DualEndpoint'
.DefaultDualEndpointBeta | 'DualEndpointBeta'
.DefaultDualEndpointEmax | 'DualEndpointEmax'
.DefaultDualEndpointRW | 'DualEndpointRW'
.DefaultDualResponsesDesign | 'DualResponsesDesign.R'
.DefaultDualResponsesSamplesDesign | 'DualResponsesSamplesDesign'
.DefaultDualSimulations | 'DualSimulations'
.DefaultDualSimulationsSummary | 'DualSimulationsSummary'
.DefaultEffFlexi | 'EffFlexi'
.DefaultEffloglog | 'Effloglog'
.DefaultFractionalCRM | 'FractionalCRM'
.DefaultGeneralModel | 'GeneralModel'
.DefaultGeneralSimulations | 'GeneralSimulations'
.DefaultGeneralSimulationsSummary | 'GeneralSimulationsSummary'
.DefaultIncrements | 'Increments'
.DefaultIncrementsDoseLevels | 'IncrementsDoseLevels'
.DefaultIncrementsHSRBeta | 'IncrementsHSRBeta'
.DefaultIncrementsMaxToxProb | 'IncrementsMaxToxProb'
.DefaultIncrementsMin | 'IncrementsMin'
.DefaultIncrementsOrdinal | 'IncrementsOrdinal'
.DefaultIncrementsRelative | 'IncrementsRelative'
.DefaultIncrementsRelativeDLT | 'IncrementsRelativeDLT'
.DefaultIncrementsRelativeDLTCurrent | 'IncrementsRelativeDLTCurrent'
.DefaultIncrementsRelativeParts | 'IncrementsRelativeParts'
.DefaultLogisticIndepBeta | 'LogisticIndepBeta'
.DefaultLogisticKadane | 'LogisticKadane'
.DefaultLogisticKadaneBetaGamma | 'LogisticKadaneBetaGamma'
.DefaultLogisticLogNormal | 'LogisticLogNormal'
.DefaultLogisticLogNormalGrouped | 'LogisticLogNormalGrouped'
.DefaultLogisticLogNormalMixture | 'LogisticLogNormalMixture'
.DefaultLogisticLogNormalOrdinal | 'LogisticLogNormalOrdinal'
.DefaultLogisticLogNormalSub | 'LogisticLogNormalSub'
.DefaultLogisticNormal | 'LogisticNormal'
.DefaultLogisticNormalFixedMixture | 'LogisticNormalFixedMixture'
.DefaultLogisticNormalMixture | 'LogisticNormalMixture'
.DefaultMcmcOptions | 'McmcOptions'
.DefaultModelEff | 'ModelEff'
.DefaultModelLogNormal | 'ModelLogNormal'
.DefaultModelParamsNormal | 'ModelParamsNormal'
.DefaultModelPseudo | 'ModelPseudo'
.DefaultModelTox | 'ModelTox'
.DefaultNextBest | 'NextBest'
.DefaultNextBestDualEndpoint | 'NextBestDualEndpoint'
.DefaultNextBestEWOC | 'NextBestEWOC'
.DefaultNextBestInfTheory | 'NextBestInfTheory'
.DefaultNextBestMaxGain | 'NextBestMaxGain'
.DefaultNextBestMaxGainSamples | 'NextBestMaxGainSamples'
.DefaultNextBestMinDist | 'NextBestMinDist'
.DefaultNextBestMTD | 'NextBestMTD'
.DefaultNextBestNCRM | 'NextBestNCRM'
.DefaultNextBestNCRMLoss | 'NextBestNCRMLoss'
.DefaultNextBestOrdinal | 'NextBestOrdinal'
.DefaultNextBestProbMTDLTE | 'NextBestProbMTDLTE'
.DefaultNextBestProbMTDMinDist | 'NextBestProbMTDMinDist'
.DefaultNextBestTD | 'NextBestTD'
.DefaultNextBestTDsamples | 'NextBestTDsamples'
.DefaultNextBestThreePlusThree | 'NextBestThreePlusThree'
.DefaultOneParExpPrior | 'OneParExpPrior'
.DefaultOneParLogNormalPrior | 'OneParLogNormalPrior'
.DefaultProbitLogNormal | 'ProbitLogNormal'
.DefaultProbitLogNormalRel | 'ProbitLogNormalRel'
.DefaultPseudoDualFlexiSimulations | 'PseudoDualFlexiSimulations'
.DefaultPseudoDualSimulations | 'PseudoDualSimulations'
.DefaultPseudoDualSimulationsSummary | 'PseudoDualSimulationsSummary'
.DefaultPseudoSimulations | 'PseudoSimulations'
.DefaultPseudoSimulationsSummary | 'PseudoSimulationsSummary'
.DefaultRuleDesign | 'RuleDesign'
.DefaultRuleDesignOrdinal | 'RuleDesignOrdinal'
.DefaultSafetyWindow | 'SafetyWindow'
.DefaultSafetyWindowConst | 'SafetyWindowConst'
.DefaultSafetyWindowSize | 'SafetyWindowSize'
.DefaultSamples | 'Samples'
.DefaultSimulations | 'Simulations'
.DefaultSimulationsSummary | 'SimulationsSummary'
.DefaultStoppingAll | 'StoppingAll'
.DefaultStoppingAny | 'StoppingAny'
.DefaultStoppingCohortsNearDose | 'StoppingCohortsNearDose'
.DefaultStoppingExternal | 'StoppingExternal'
.DefaultStoppingHighestDose | 'StoppingHighestDose'
.DefaultStoppingList | 'StoppingList'
.DefaultStoppingLowestDoseHSRBeta | 'StoppingLowestDoseHSRBeta'
.DefaultStoppingMaxGainCIRatio | 'StoppingMaxGainCIRatio'
.DefaultStoppingMinCohorts | 'StoppingMinCohorts'
.DefaultStoppingMinPatients | 'StoppingMinPatients'
.DefaultStoppingMissingDose | 'StoppingMissingDose'
.DefaultStoppingMTDCV | 'StoppingMTDCV'
.DefaultStoppingMTDdistribution | 'StoppingMTDdistribution'
.DefaultStoppingOrdinal | 'StoppingOrdinal'
.DefaultStoppingPatientsNearDose | 'StoppingPatientsNearDose'
.DefaultStoppingSpecificDose | 'StoppingSpecificDose'
.DefaultStoppingTargetBiomarker | 'StoppingTargetBiomarker'
.DefaultStoppingTargetProb | 'StoppingTargetProb'
.DefaultStoppingTDCIRatio | 'StoppingTDCIRatio'
.DefaultTDDesign | 'TDDesign'
.DefaultTDsamplesDesign | 'TDsamplesDesign'
.DefaultTITELogisticLogNormal | 'TITELogisticLogNormal'
.Design | 'Design'
.DesignGrouped | 'DesignGrouped'
.DesignOrdinal | 'DesignOrdinal'
.DualDesign | 'DualDesign'
.DualEndpoint | 'DualEndpoint'
.DualEndpointBeta | 'DualEndpointBeta'
.DualEndpointEmax | 'DualEndpointEmax'
.DualEndpointRW | 'DualEndpointRW'
.DualResponsesDesign | 'DualResponsesDesign.R'
.DualResponsesSamplesDesign | 'DualResponsesSamplesDesign'
.DualSimulations | 'DualSimulations'
.DualSimulationsSummary | 'DualSimulationsSummary'
.EffFlexi | 'EffFlexi'
.Effloglog | 'Effloglog'
.FractionalCRM | 'FractionalCRM'
.GeneralData | 'GeneralData'
.GeneralModel | 'GeneralModel'
.GeneralSimulations | 'GeneralSimulations'
.GeneralSimulationsSummary | 'GeneralSimulationsSummary'
.IncrementsDoseLevels | 'IncrementsDoseLevels'
.IncrementsHSRBeta | 'IncrementsHSRBeta'
.IncrementsMaxToxProb | 'IncrementsMaxToxProb'
.IncrementsMin | 'IncrementsMin'
.IncrementsOrdinal | 'IncrementsOrdinal'
.IncrementsRelative | 'IncrementsRelative'
.IncrementsRelativeDLT | 'IncrementsRelativeDLT'
.IncrementsRelativeDLTCurrent | 'IncrementsRelativeDLTCurrent'
.IncrementsRelativeParts | 'IncrementsRelativeParts'
.LogisticIndepBeta | 'LogisticIndepBeta'
.LogisticKadane | 'LogisticKadane'
.LogisticKadaneBetaGamma | 'LogisticKadaneBetaGamma'
.LogisticLogNormal | 'LogisticLogNormal'
.LogisticLogNormalGrouped | 'LogisticLogNormalGrouped'
.LogisticLogNormalMixture | 'LogisticLogNormalMixture'
.LogisticLogNormalOrdinal | 'LogisticLogNormalOrdinal'
.LogisticLogNormalSub | 'LogisticLogNormalSub'
.LogisticNormal | 'LogisticNormal'
.LogisticNormalFixedMixture | 'LogisticNormalFixedMixture'
.LogisticNormalMixture | 'LogisticNormalMixture'
.McmcOptions | 'McmcOptions'
.ModelEff | 'ModelEff'
.ModelLogNormal | 'ModelLogNormal'
.ModelParamsNormal | 'ModelParamsNormal'
.ModelPseudo | 'ModelPseudo'
.ModelTox | 'ModelTox'
.NextBestDualEndpoint | 'NextBestDualEndpoint'
.NextBestEWOC | 'NextBestEWOC'
.NextBestInfTheory | 'NextBestInfTheory'
.NextBestMaxGain | 'NextBestMaxGain'
.NextBestMaxGainSamples | 'NextBestMaxGainSamples'
.NextBestMinDist | 'NextBestMinDist'
.NextBestMTD | 'NextBestMTD'
.NextBestNCRM | 'NextBestNCRM'
.NextBestNCRMLoss | 'NextBestNCRMLoss'
.NextBestOrdinal | 'NextBestOrdinal'
.NextBestProbMTDLTE | 'NextBestProbMTDLTE'
.NextBestProbMTDMinDist | 'NextBestProbMTDMinDist'
.NextBestTD | 'NextBestTD'
.NextBestTDsamples | 'NextBestTDsamples'
.NextBestThreePlusThree | 'NextBestThreePlusThree'
.OneParExpPrior | 'OneParExpPrior'
.OneParLogNormalPrior | 'OneParLogNormalPrior'
.ProbitLogNormal | 'ProbitLogNormal'
.ProbitLogNormalRel | 'ProbitLogNormalRel'
.PseudoDualFlexiSimulations | 'PseudoDualFlexiSimulations'
.PseudoDualSimulations | 'PseudoDualSimulations'
.PseudoDualSimulationsSummary | 'PseudoDualSimulationsSummary'
.PseudoSimulations | 'PseudoSimulations'
.PseudoSimulationsSummary | 'PseudoSimulationsSummary'
.RuleDesign | 'RuleDesign'
.RuleDesignOrdinal | 'RuleDesignOrdinal'
.SafetyWindowConst | 'SafetyWindowConst'
.SafetyWindowSize | 'SafetyWindowSize'
.Samples | 'Samples'
.Simulations | 'Simulations'
.SimulationsSummary | 'SimulationsSummary'
.StoppingAll | 'StoppingAll'
.StoppingAny | 'StoppingAny'
.StoppingCohortsNearDose | 'StoppingCohortsNearDose'
.StoppingExternal | 'StoppingExternal'
.StoppingHighestDose | 'StoppingHighestDose'
.StoppingList | 'StoppingList'
.StoppingLowestDoseHSRBeta | 'StoppingLowestDoseHSRBeta'
.StoppingMaxGainCIRatio | 'StoppingMaxGainCIRatio'
.StoppingMinCohorts | 'StoppingMinCohorts'
.StoppingMinPatients | 'StoppingMinPatients'
.StoppingMissingDose | 'StoppingMissingDose'
.StoppingMTDCV | 'StoppingMTDCV'
.StoppingMTDdistribution | 'StoppingMTDdistribution'
.StoppingOrdinal | 'StoppingOrdinal'
.StoppingPatientsNearDose | 'StoppingPatientsNearDose'
.StoppingSpecificDose | 'StoppingSpecificDose'
.StoppingTargetBiomarker | 'StoppingTargetBiomarker'
.StoppingTargetProb | 'StoppingTargetProb'
.StoppingTDCIRatio | 'StoppingTDCIRatio'
.TDDesign | 'TDDesign'
.TDsamplesDesign | 'TDsamplesDesign'
.TITELogisticLogNormal | 'TITELogisticLogNormal'
|-method | Combine Two Stopping Rules with OR
|-method | Combine an Atomic Stopping Rule and a Stopping List with OR
|-method | Combine a Stopping List and an Atomic Stopping Rule with OR