blq_trans               A transform for ggplot2 with data that may be
                        below the lower limit of quantification
breaks_blq_general      Generate breaks for measurements below the
                        limit of quantification
calc_derived            Calculate derived pharmacokinetic parameters
                        for a 1-, 2-, or 3-compartment linear model.
calc_sd_1cmt            Calculate C(t) for a 1-compartment linear model
calc_sd_2cmt            Calculate C(t) for a 2-compartment linear model
calc_sd_3cmt            Calculate C(t) for a 3-compartment linear model
calc_ss_1cmt            Calculate C(t) for a 1-compartment linear model
                        at steady-state
calc_ss_2cmt            Calculate C(t) for a 2-compartment linear model
                        at steady-state
calc_ss_3cmt            Calculate C(t) for a 3-compartment linear model
                        at steady-state
count_na                Count the number of NA values in a vector.
dgr_table               Generate a summary table of descriptive data
                        for every individual in a dataset suitable for
                        tabulation in a report.
estimate_lloq           Estimate the lower limit of quantification
                        (LLOQ) from a vector
fmt_signif              Format a number with the correct number of
                        significant digits and trailing zeroes.
ftrans_blq_linear       Forward transformation for linear BLQ data
gcv                     Calculate a geometric coefficient of variation.
gcv_convert             Convert geometric variance or standard
                        deviation to a geometric coefficient of
                        variation
get_auc                 Calculate the area under the curve (AUC) for
                        each subject over the time interval for
                        dependent variables ('dv') using the
                        trapezoidal rule.
get_est_table           Create a table of model parameter estimates
                        from a NONMEM output object.
get_omega               Extract variability parameter estimates from a
                        NONMEM output object.
get_probinfo            Extract problem and estimation information from
                        a NONMEM output object.
get_shrinkage           Extract shrinkage estimates from a NONMEM
                        output object.
get_sigma               Extract residual variability parameter
                        estimates from a NONMEM output object.
get_theta               Extract structural model parameter estimates
                        and associated information from a NONMEM output
                        object.
gm                      Calculate geometric mean
itrans_blq_linear       Inverse transformation for linear BLQ data
label_blq               Label axes with censoring labels for BLQ
pcv                     Calculate percentage coefficient of variation
pk_curve                Provide concentration-time curves.
plot_dist               Plot a distribution as a hybrid containing a
                        halfeye, a boxplot and jittered points.
plot_nmprogress         Plot NONMEM parameter estimation by iteration.
plot_scm                Visualize PsN SCM output.
read_nm                 Read NONMEM 7.2+ output into a list of lists.
read_nm_all             Read all NONMEM files for a single NONMEM run.
read_nm_multi_table     Read (single or) multiple NONMEM tables from a
                        single file
read_nm_std_ext         Read a standard NONMEM extension file
read_nmcov              Read in the NONMEM variance-covariance matrix.
read_nmext              Read NONMEM output into a list.
read_nmtables           Reads NONMEM output tables.
read_scm                Read PsN SCM output into a format suitable for
                        further use.
rnm                     Read NONMEM 7.2+ output into an R object.
sample_omega            Sample from the multivariate normal
                        distribution using the OMEGA
                        variance-covariance matrix to generate new sets
                        of simulated ETAs from NONMEM output.
sample_sigma            Sample from the multivariate normal
                        distribution using the SIGMA
                        variance-covariance matrix to generate new sets
                        of simulated EPSILONs from NONMEM output.
sample_uncert           Sample from the multivariate normal
                        distribution to generate new sets of parameters
                        from NONMEM output.
table_rtf               Read NONMEM output into a list.
