PKNCA                   Compute noncompartmental pharmacokinetics
PKNCA.choose.option     Choose either the value from an option list or
                        the current set value for an option.
PKNCA.options           Set default options for PKNCA functions
PKNCA.options.describe
                        Describe a PKNCA.options option by name.
PKNCA.set.summary       Define how NCA parameters are summarized.
PKNCA_impute_fun_list   Separate out a vector of PKNCA imputation
                        methods into a list of functions
PKNCA_impute_method     Methods for imputation of data with PKNCA
PKNCAconc               Create a PKNCAconc object
PKNCAdata               Create a PKNCAdata object.
PKNCAdose               Create a PKNCAdose object
PKNCAresults            Generate a PKNCAresults object
add.interval.col        Add columns for calculations within PKNCA
                        intervals
addProvenance           Add a hash and associated information to enable
                        checking object provenance.
adj.r.squared           Calculate the adjusted r-squared value
any_sparse_dense_in_interval
                        Determine if there are any sparse or dense
                        calculations requested within an interval
as.data.frame.PKNCAresults
                        Extract the parameter results from a
                        PKNCAresults and return them as a data.frame.
as_PKNCAconc            Convert an object into a PKNCAconc object
as_sparse_pk            Generate a sparse_pk object
assert_PKNCAdata        Assert that an object is a PKNCAdata object
assert_aucmethod        Assert that a value is a valid AUC method
assert_conc             Verify that concentration measurements are
                        valid
assert_dosetau          Assert that a value is a dosing interval
assert_intervals        Assert Intervals
assert_intervaltime_single
                        Assert that an interval is accurately defined
                        as an interval, and return the interval
assert_lambdaz          Assert that a lambda.z value is valid
assert_number_between   Confirm that a value is greater than another
                        value
assert_numeric_between
                        Confirm that a value is greater than another
                        value
assert_unit_col         Assert that a value may either be a column name
                        in the data (first) or a single unit value
                        (second)
auc_integrate           Support function for AUC integration
business.mean           Generate functions to do the named function
                        (e.g. mean) applying the business rules.
check.conversion        Check that the conversion to a data type does
                        not change the number of NA values
check.interval.deps     Take in a single row of an interval
                        specification and return that row updated with
                        any additional calculations that must be done
                        to fulfill all dependencies.
check.interval.specification
                        Check the formatting of a calculation interval
                        specification data frame.
checkProvenance         Check the hash of an object to confirm its
                        provenance.
choose.auc.intervals    Choose intervals to compute AUCs from time and
                        dosing information
choose_interval_method
                        Choose how to interpolate, extrapolate, or
                        integrate data in each concentration interval
clean.conc.blq          Handle BLQ values in the concentration
                        measurements as requested by the user.
clean.conc.na           Handle NA values in the concentration
                        measurements as requested by the user.
cov_holder              Calculate the covariance for two time points
                        with sparse sampling
defunct                 The following functions are defunct
exclude                 Exclude data points or results from
                        calculations or summarization.
exclude_nca             Exclude NCA parameters based on examining the
                        parameter set.
exclude_nca_by_param    Exclude NCA Results Based on Parameter
                        Thresholds
filter.PKNCAresults     dplyr filtering for PKNCA
find.tau                Find the repeating interval within a vector of
                        doses
findOperator            Find the first occurrence of an operator in a
                        formula and return the left, right, or both
                        sides of the operator.
fit_half_life           Perform the half-life fit given the data.  The
                        function simply fits the data without any
                        validation.  No selection of points or any
                        other components are done.
formula.PKNCAconc       Extract the formula from a PKNCAconc object.
geomean                 Compute the geometric mean, sd, and CV
get.best.model          Extract the best model from a list of models
                        using the AIC.
get.first.model         Get the first model from a list of models
get.interval.cols       Get the columns that can be used in an interval
                        specification
get.parameter.deps      Get all columns that depend on a parameter
getAttributeColumn      Retrieve the value of an attribute column.
getColumnValueOrNot     Get the value from a column in a data frame if
                        the value is a column there, otherwise, the
                        value should be a scalar or the length of the
                        data.
getDataName.PKNCAconc   Get the name of the element containing the data
                        for the current object.
getDepVar               Get the dependent variable (left hand side of
                        the formula) from a PKNCA object.
getGroups.PKNCAconc     Get the groups (right hand side after the '|'
                        from a PKNCA object).
getIndepVar             Get the independent variable (right hand side
                        of the formula) from a PKNCA object.
get_halflife_points     Determine which concentrations were used for
                        half-life calculation
get_impute_method       Get the impute function from either the
                        intervals column or from the method
group_by.PKNCAresults   dplyr grouping for PKNCA
group_vars.PKNCAconc    Get grouping variables for a PKNCA object
inner_join.PKNCAresults
                        dplyr joins for PKNCA
interp.extrap.conc      Interpolate concentrations between measurements
                        or extrapolate concentrations after the last
                        measurement.
interp_extrap_conc_method
                        Interpolate or extrapolate concentrations using
                        the provided method
is_sparse_pk.PKNCAconc
                        Is a PKNCA object used for sparse PK?
model.frame.PKNCAconc   Extract the columns used in the formula (in
                        order) from a PKNCAconc or PKNCAdose object.
mutate.PKNCAresults     dplyr mutate-based modification for PKNCA
normalize_exclude       Normalize the exclude column by setting blanks
                        to NA
parse_formula_to_cols   Convert a formula representation to the columns
                        for input data
pk.business             Run any function with a maximum missing
                        fraction of X and 0s possibly counting as
                        missing.  The maximum fraction missing comes
                        from 'PKNCA.options("max.missing")'.
pk.calc.ae              Calculate amount excreted (typically in urine
                        or feces)
pk.calc.aucabove        Calculate the AUC above a given concentration
pk.calc.aucint          Calculate the AUC over an interval with
                        interpolation and/or extrapolation of
                        concentrations for the beginning and end of the
                        interval.
pk.calc.auciv           Calculate AUC for intravenous dosing
pk.calc.aucpext         Calculate the AUC percent extrapolated
pk.calc.auxc            A compute the Area Under the (Moment) Curve
pk.calc.c0              Estimate the concentration at dosing time for
                        an IV bolus dose.
pk.calc.cav             Calculate the average concentration during an
                        interval.
pk.calc.ceoi            Determine the concentration at the end of
                        infusion
pk.calc.cl              Calculate the (observed oral) clearance
pk.calc.clast.obs       Determine the last observed concentration above
                        the limit of quantification (LOQ).
pk.calc.clr             Calculate renal clearance
pk.calc.cmax            Determine maximum observed PK concentration
pk.calc.count_conc      Count the number of concentration measurements
                        in an interval
pk.calc.cstart          Determine the concentration at the beginning of
                        the interval
pk.calc.ctrough         Determine the trough (end of interval)
                        concentration
pk.calc.deg.fluc        Determine the degree of fluctuation
pk.calc.dn              Determine dose normalized NCA parameter
pk.calc.f               Calculate the absolute (or relative)
                        bioavailability
pk.calc.fe              Calculate fraction excreted (typically in urine
                        or feces)
pk.calc.half.life       Compute the half-life and associated parameters
pk.calc.kel             Calculate the elimination rate (Kel)
pk.calc.mrt             Calculate the mean residence time (MRT) for
                        single-dose data or linear multiple-dose data.
pk.calc.mrt.md          Calculate the mean residence time (MRT) for
                        multiple-dose data with nonlinear kinetics.
pk.calc.ptr             Determine the peak-to-trough ratio
pk.calc.sparse_auc      Calculate AUC and related parameters using
                        sparse NCA methods
pk.calc.swing           Determine the PK swing
pk.calc.thalf.eff       Calculate the effective half-life
pk.calc.time_above      Determine time at or above a set value
pk.calc.tlag            Determine the observed lag time (time before
                        the first concentration above the limit of
                        quantification or above the first concentration
                        in the interval)
pk.calc.tlast           Determine time of last observed concentration
                        above the limit of quantification.
pk.calc.tmax            Determine time of maximum observed PK
                        concentration
pk.calc.totdose         Extract the dose used for calculations
pk.calc.vss             Calculate the steady-state volume of
                        distribution (Vss)
pk.calc.vz              Calculate the terminal volume of distribution
                        (Vz)
pk.nca                  Compute NCA parameters for each interval for
                        each subject.
pk.nca.interval         Compute all PK parameters for a single
                        concentration-time data set
pk.nca.intervals        Compute NCA for multiple intervals
pk.tss                  Compute the time to steady-state (tss)
pk.tss.data.prep        Clean up the time to steady-state parameters
                        and return a data frame for use by the tss
                        calculators.
pk.tss.monoexponential
                        Compute the time to steady state using
                        nonlinear, mixed-effects modeling of trough
                        concentrations.
pk.tss.monoexponential.individual
                        A helper function to estimate individual and
                        single outputs for monoexponential time to
                        steady-state.
pk.tss.monoexponential.population
                        A helper function to estimate population and
                        popind outputs for monoexponential time to
                        steady-state.
pk.tss.stepwise.linear
                        Compute the time to steady state using stepwise
                        test of linear trend
pk_nca_result_to_df     Convert the grouping info and list of results
                        for each group into a results data.frame
pknca_find_units_param
                        Find NCA parameters with a given unit type
pknca_unit_conversion   Perform unit conversion (if possible) on PKNCA
                        results
pknca_units_add_paren   Add parentheses to a unit value, if needed
pknca_units_table       Create a unit assignment and conversion table
print.PKNCAconc         Print and/or summarize a PKNCAconc or PKNCAdose
                        object.
print.PKNCAdata         Print a PKNCAdata object
print.provenance        Print the summary of a provenance object
print.summary_PKNCAresults
                        Print the results summary
roundString             Round a value to a defined number of digits
                        printing out trailing zeros, if applicable.
roundingSummarize       During the summarization of PKNCAresults, do
                        the rounding of values based on the
                        instructions given.
setAttributeColumn      Add an attribute to an object where the
                        attribute is added as a name to the names of
                        the object.
setDuration.PKNCAconc   Set the duration of dosing or measurement
setExcludeColumn        Set the exclude parameter on an object
setRoute                Set the dosing route
set_intervals           Set Intervals
signifString            Round a value to a defined number of
                        significant digits printing out trailing zeros,
                        if applicable.
sort.interval.cols      Sort the interval columns by dependencies.
sparse_auc_weight_linear
                        Calculate the weight for sparse AUC calculation
                        with the linear-trapezoidal rule
sparse_mean             Calculate the mean concentration at all time
                        points for use in sparse NCA calculations
sparse_pk_attribute     Set or get a sparse_pk object attribute
sparse_to_dense_pk      Extract the mean concentration-time profile as
                        a data.frame
summary.PKNCAdata       Summarize a PKNCAdata object showing important
                        details about the concentration, dosing, and
                        interval information.
summary.PKNCAresults    Summarize PKNCA results
superposition           Compute noncompartmental superposition for
                        repeated dosing
time_calc               Times relative to an event (typically dosing)
tss.monoexponential.generate.formula
                        A helper function to generate the formula and
                        starting values for the parameters in
                        monoexponential models.
var_sparse_auc          Calculate the variance for the AUC of sparsely
                        sampled PK
