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Automatic import of run output

Import tables and output files from a NLME run to R.

xpose_data()
Import NONMEM output into R

Manual import of run output

Manually import tables and output files from a NLME run to R.

read_nm_files()
NONMEM output file import function
read_nm_model()
NONMEM model file parser
manual_nm_import()
Manually define nonmem tables to be imported
list_nm_tables()
List NONMEM output tables
read_nm_tables()
NONMEM output table import function

xpdb examples

Example of xpose_data

xpdb_ex_pk
xpose_data examples

Data summary

Summarize the xpdb content or the run

print(<xpose_data>)
Print an xpose_data object
summary(<xpose_data>)
Summarizing xpose_data
prm_table()
Display a parameter estimates to the console
list_vars()
List available variables
list_data() list_files() list_special()
List available datasets

Edit xpdb content

Edit data, index or files within an xpdb

filter(<xpose_data>) slice(<xpose_data>) distinct(<xpose_data>)
Subset datasets in an xpdb
mutate(<xpose_data>) select(<xpose_data>) rename(<xpose_data>)
Add, remove or rename variables in an xpdb
group_by(<xpose_data>) ungroup(<xpose_data>) summarise(<xpose_data>) summarize(<xpose_data>)
Group/ungroup and summarize variables in an xpdb
irep()
Add simulation counter
set_var_types() set_var_labels() set_var_units()
Set variable type, label or units

Access data from an xpdb

Access code, data, files or summary from an xpdb object

get_code()
Access model code
get_data()
Access model output table data
get_file()
Access model output file data
get_prm()
Access model parameters
get_special()
Access special model data
get_summary()
Access model summary data

Basic gof

Basic goodness-of-fit plots.

res_vs_idv() absval_res_vs_idv()
Residuals plotted against the independent variable
res_vs_pred() absval_res_vs_pred()
Residuals plotted against population predictions
dv_vs_ipred() dv_vs_pred()
Observations plotted against model predictions
dv_vs_idv() ipred_vs_idv() pred_vs_idv() dv_preds_vs_idv()
Observations and model predictions plotted against the independent variable

Indiviudal plots

Indiviudal observations and model predictions profiles by the independent variable

ind_plots()
Observations, individual predictions and population predictions plotted against the independent variable for every individual

Visual predictive checks

Visual predictive checks data and plot generation

vpc_data()
Visual predictive checks data
vpc_opt()
Generate a list of options for VPC data generation
vpc()
Visual predictive checks

Distribution plots

Covariate, parameters, etas and residuals distribution plots

prm_distrib() eta_distrib() res_distrib() cov_distrib()
Distribution plots of ETA and parameters

QQ plots

Covariate, parameters, etas and residuals QQ plots

prm_qq() eta_qq() res_qq() cov_qq()
QQ plots of ETA and residuals

Kinetic plots

Plots of compartments’ amount

amt_vs_idv()
Compartment kinetics

Minimization diagnostics

Graphics to evaluate the estimation step

prm_vs_iteration() grd_vs_iteration()
Parameter value or gradient vs. iterations

General plotting functions

Functions to manually create customized plots from an xpose_data object.

xplot_distrib()
Default xpose distribution plot function
xplot_qq()
Default xpose QQ plot function
xplot_scatter()
Default xpose scatter plot function
data_opt()
Create options for data import

Customize plots

Add, customize themes or template titles.

template_titles
Template titles
update_themes()
Create xpose theme
theme_bw2() theme_readable()
An additional set of themes for ggplot2
theme_xp_default() theme_xp_xpose4()
A set of xpose themes

Print plots to the console or save them into a file.

print(<xpose_plot>)
Draw an xpose_plot object
xpose_save()
Save xpose plot