Package index • pmxTools

All functions
`blq_trans()` `blq_log_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()` `calc_derived_1cpt()` `calc_derived_2cpt()` `calc_derived_3cpt()`	Calculate derived pharmacokinetic parameters for a 1-, 2-, or 3-compartment linear model.
`calc_sd_1cmt()` `calc_sd_1cmt_linear_bolus()` `calc_sd_1cmt_linear_oral_1_lag()` `calc_sd_1cmt_linear_infusion()` `calc_sd_1cmt_linear_oral_0()` `calc_sd_1cmt_linear_oral_1()` `calc_sd_1cmt_linear_oral_0_lag()`	Calculate C(t) for a 1-compartment linear model
`calc_sd_2cmt()` `calc_sd_2cmt_linear_bolus()` `calc_sd_2cmt_linear_oral_1_lag()` `calc_sd_2cmt_linear_infusion()` `calc_sd_2cmt_linear_oral_0_lag()` `calc_sd_2cmt_linear_oral_1()` `calc_sd_2cmt_linear_oral_0()`	Calculate C(t) for a 2-compartment linear model
`calc_sd_3cmt()` `calc_sd_3cmt_linear_bolus()` `calc_sd_3cmt_linear_oral_1_lag()` `calc_sd_3cmt_linear_infusion()` `calc_sd_3cmt_linear_oral_0()` `calc_sd_3cmt_linear_oral_0_lag()` `calc_sd_3cmt_linear_oral_1()`	Calculate C(t) for a 3-compartment linear model
`calc_ss_1cmt()` `calc_ss_1cmt_linear_bolus()` `calc_ss_1cmt_linear_infusion()` `calc_ss_1cmt_linear_oral_0()` `calc_ss_1cmt_linear_oral_0_lag()` `calc_ss_1cmt_linear_oral_1_lag()` `calc_ss_1cmt_linear_oral_1()`	Calculate C(t) for a 1-compartment linear model at steady-state
`calc_ss_2cmt()` `calc_ss_2cmt_linear_bolus()` `calc_ss_2cmt_linear_infusion()` `calc_ss_2cmt_linear_oral_0()` `calc_ss_2cmt_linear_oral_1_lag()` `calc_ss_2cmt_linear_oral_0_lag()` `calc_ss_2cmt_linear_oral_1()`	Calculate C(t) for a 2-compartment linear model at steady-state
`calc_ss_3cmt()` `calc_ss_3cmt_linear_bolus()` `calc_ss_3cmt_linear_oral_1_lag()` `calc_ss_3cmt_linear_infusion()` `calc_ss_3cmt_linear_oral_0()` `calc_ss_3cmt_linear_oral_0_lag()` `calc_ss_3cmt_linear_oral_1()`	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()` `ftrans_blq_log()`	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()` `itrans_blq_log()`	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.

Reference

All functions