Arm                     Create a treatment arm.
BinomialDistribution    Binomial distribution.
Bolus                   Create one or several bolus(es).
Bootstrap               Create a bootstrap object.
BootstrapDistribution   Create a bootstrap distribution. During
                        function sampling, CAMPSIS will generate values
                        depending on the given data and arguments.
ConstantDistribution    Create a constant distribution. Its value will
                        be constant across all generated samples.
Covariate               Create a non time-varying (fixed) covariate.
CyclicSchedule          Cyclic schedule constructor.
Dataset                 Create a dataset.
DatasetConfig           Create a dataset configuration. This
                        configuration allows CAMPSIS to know which are
                        the default depot and observed compartments.
Declare                 Create declare settings.
DiscreteDistribution    Discrete distribution.
DoseAdaptation          Create a dose adaptation.
EtaDistribution         Create an ETA distribution. The resulting
                        distribution is a normal distribution, with
                        mean=0 and sd=sqrt(OMEGA).
Event                   Create an interruption event.
EventCovariate          Create an event covariate. These covariates can
                        be modified further in interruption events.
Events                  Create a list of interruption events.
FixedDistribution       Create a fixed distribution. Each sample will
                        be assigned a fixed value coming from vector
                        'values'.
FunctionDistribution    Create a function distribution. During
                        distribution sampling, the provided function
                        will be responsible for generating values for
                        each sample. If first argument of this function
                        is not the size (n), please tell which argument
                        corresponds to the size 'n' (e.g.
                        list(size="n")).
Hardware                Create hardware settings.
IOV                     Define inter-occasion variability (IOV) into
                        the dataset. A new variable of name 'colname'
                        will be output into the dataset and will vary
                        at each dose number according to the given
                        distribution.
Infusion                Create one or several infusion(s).
LogNormalDistribution   Create a log normal distribution.
NOCB                    Create NOCB settings.
NormalDistribution      Create a normal distribution.
Observations            Create an observations list. Please note that
                        the provided 'times' will automatically be
                        sorted. Duplicated times will be removed.
Occasion                Define a new occasion. Occasions are defined by
                        mapping occasion values to dose numbers. A new
                        column will automatically be created in the
                        exported dataset.
Outfun                  Create a new output function
PI                      Compute the prediction interval summary over
                        time.
ParameterDistribution   Create a parameter distribution. The resulting
                        distribution is a log-normal distribution, with
                        meanlog=log(THETA) and sdlog=sqrt(OMEGA).
Progress                Create progress settings.
RepeatAtSchedule        'Repeat at' schedule constructor. Note that the
                        time 0 for the base pattern will be added by
                        default if not provided.
Scenario                Create an scenario.
Scenarios               Create a list of scenarios.
Settings                Create advanced simulation settings.
SimulationProgress      Create a simulation progress object.
Solver                  Create solver settings.
TimeVaryingCovariate    Create a time-varying covariate. This covariate
                        will be implemented using EVID=2 rows in the
                        exported dataset and will not use interruption
                        events.
UniformDistribution     Create an uniform distribution.
VPC                     Compute the VPC summary. Input data frame must
                        contain the following columns: - replicate:
                        replicate number - low: low percentile value in
                        replicate (and in scenario if present) - med:
                        median value in replicate (and in scenario if
                        present) - up: up percentile value in replicate
                        (and in scenario if present) - any scenario
                        column
applyCompartmentCharacteristics
                        Apply compartment characteristics from model.
                        In practice, only compartment infusion duration
                        needs to be applied.
arm-class               Arm class.
arms-class              Arms class.
bolus-class             Bolus class.
bolus_wrapper-class     Bolus wrapper class.
bootstrap-class         Bootstrap class.
bootstrap_distribution-class
                        Bootstrap distribution class.
campsis_handler         Suggested Campsis handler for showing the
                        progress bar.
constant_distribution-class
                        Constant distribution class.
convertTime             Convert numeric time vector based on the
                        provided units.
covariate-class         Covariate class.
covariates-class        Covariates class.
cyclic_schedule-class   Cyclic schedule class.
dataset-class           Dataset class.
dataset_config-class    Dataset configuration class.
days                    Convert days to hours.
declare_settings-class
                        Declare settings class.
distribution-class      Distribution class. See this class as an
                        interface.
dose_adaptation-class   Dose adaptation class.
dose_adaptations-class
                        Dose adaptations class.
dosingOnly              Filter CAMPSIS output on dosing rows.
event-class             Event class.
event_covariate-class   Event covariate class.
events-class            Events class.
fixed_covariate-class   Fixed covariate class.
fixed_distribution-class
                        Fixed distribution class.
function_distribution-class
                        Function distribution class.
generateIIV             Generate IIV matrix for the given Campsis
                        model.
generateIIV_            Generate IIV matrix for the given OMEGA matrix.
getAvailableTimeUnits   Return the list of available time units.
getCovariates           Get all covariates (fixed / time-varying /
                        event covariates).
getEventCovariates      Get all event-related covariates.
getFixedCovariates      Get all fixed covariates.
getIOVs                 Get all IOV objects.
getOccasions            Get all occasions.
getSeedForDatasetExport
                        Get seed for dataset export.
getSeedForIteration     Get seed for iteration.
getSeedForParametersSampling
                        Get seed for parameter uncertainty sampling.
getSplittingConfiguration
                        Get splitting configuration for parallel
                        export.
getTimeVaryingCovariates
                        Get all time-varying covariates.
getTimes                Get all distinct times for the specified
                        object.
hardware_settings-class
                        Hardware settings class.
hours                   Convert hours to hours (do nothing).
infusion-class          Infusion class.
infusion_wrapper-class
                        Infusion wrapper class.
internal_settings-class
                        Internal settings class (transient object from
                        the simulation settings).
length,arm-method       Return the number of subjects contained in this
                        arm.
length,cyclic_schedule-method
                        Return the number of repetition cycles.
length,dataset-method   Return the number of subjects contained in this
                        dataset.
length,repeat_at_schedule-method
                        Return the number of repetition cycles.
minutes                 Convert minutes to hours.
months                  Convert pharma months (1 month = 4 weeks) to
                        hours.
mrgsolve_engine-class   mrgsolve engine class.
nhanes                  NHANES database (demographics and body measure
                        data combined, from 2017-2018).
nocb_settings-class     NOCB settings class.
obsOnly                 Filter CAMPSIS output on observation rows.
observations-class      Observations class.
observations_set-class
                        Observations set class.
occasion-class          Occasion class.
occasions-class         Occasions class.
output_function-class   Output function class.
progress_settings-class
                        Progress settings class.
protocol-class          Protocol class.
repeatSchedule          Repeat schedule.
repeat_at_schedule-class
                        'Repeat at' schedule class.
repeated_schedule-class
                        Repeated schedule class. See this class as an
                        interface.
retrieveParameterValue
                        Retrieve the parameter value (standardized) for
                        the specified parameter name.
rxode_engine-class      RxODE/rxode2 engine class.
sample                  Sample generic object.
scatterPlot             Scatter plot (or X vs Y plot).
scenario-class          Scenario class.
scenarios-class         Scenarios class.
seconds                 Convert seconds to hours.
setLabel                Set the label.
setSubjects             Set the number of subjects.
setupPlanDefault        Setup default plan for the given simulation or
                        hardware settings. This plan will prioritise
                        the distribution of workers in the following
                        order: 1) Replicates (if 'replicate_parallel'
                        is enabled) 2) Scenarios (if
                        'scenario_parallel' is enabled) 3) Dataset
                        export / slices (if 'dataset_export' or
                        'slice_parallel' is enabled)
setupPlanSequential     Setup plan as sequential (i.e. no
                        parallelisation).
shadedPlot              Shaded plot (or prediction interval plot).
simulate                Simulate function.
simulation_engine-class
                        Simulation engine class.
simulation_progress-class
                        Simulation progress class.
simulation_settings-class
                        Simulation settings class.
solver_settings-class   Solver settings class. See ?mrgsolve::update.
                        See ?rxode2::rxSolve.
spaghettiPlot           Spaghetti plot.
standardiseTime         Standardise time to hours.
time_varying_covariate-class
                        Time-varying covariate class.
treatment-class         Treatment class.
treatment_iov-class     Treatment IOV class.
treatment_iovs-class    Treatment IOV's class.
undefined_distribution-class
                        Undefined distribution class. This type of
                        object is automatically created in method
                        toExplicitDistribution() when the user does not
                        provide a concrete distribution. This is
                        because S4 objects do not accept NULL values.
undefined_schedule-class
                        Undefined schedule class.
unwrapTreatment         Unwrap treatment.
updateADDL              Update the number of additional doses (ADDL).
updateAmount            Update amount.
updateII                Update the inter-dose interval (II).
updateRepeat            Update the repeat field (argument 'rep' in
                        Bolus and Infusion constructors).
vpcPlot                 VPC plot.
weeks                   Convert weeks to hours.
years                   Convert pharma years (1 year = 12*4 weeks) to
                        hours.
