Function reference • xgxr

All functions
`StatSmoothOrdinal`	Stat object for producing smooths through ordinal data
`StatSummaryBinQuant`	Stat ggproto object for binning by quantile for xgx_stat_ci
`StatSummaryOrdinal`	Stat ggproto object for creating ggplot layers of binned confidence intervals for probabiliities of classes in ordinal data
`case1_pkpd`	Case 1 PKPD Data Set
`edit_rmd_template_str()`	Edit a Rmd Template from xgx
`get_rmd_name()`	Determine the name of a Rmd template
`get_rmd_str()`	`get_rmd_str` returns a Rmd template string, based on the desired PKPD parameters
`mad`	Multiple Ascending Dose Data Set
`mad_missing_duplicates`	Multiple Ascending Dose Data Set (Duplicates Removed)
`mad_nca`	Multiple Ascending Dose Noncompartmental Analysis (NCA) dataset
`nlmixr_theo_sd`	nlmixr Theophylline SD Data Set
`predict(<nls>)`	predict.nls
`predictdf()`	Prediction data frame from ggplot2 Get predictions with standard errors into data frame
`predictdf(<nls>)`	Prediction data frame for nls
`predictdf(<polr>)`	Prediction data frame for polr
`sad`	Single Ascending Dose Data Set
`theme_xgx()`	Calls the standard theme for xGx graphics
`xgx_annotate_filenames()`	Append filenames to bottom of the plot
`xgx_annotate_status()`	Create a status (e.g. DRAFT) annotation layer
`xgx_annotate_status_png()`	Annotate a png file or directory of png files
`xgx_auto_explore()`	Produce an xgx-styled report the given dataset using xgx R markdown templates, or a user-provided R markdown template. (Note: The R markdown template provided must be formatted in a similar manner to that of the xgx R markdown templates to work.) The working directory will contain a new directory (`xgx_autoexplore_output`) after running this function, which will contain a directory for the dataset, and futher a directory for the type of analysis / R markdown template.
`xgx_breaks_log10()`	Sets the default breaks for log10
`xgx_breaks_time()`	Sets the default breaks for a time axis
`xgx_check_data()`	Check data for various issues
`xgx_conf_int()`	`xgx_conf_int` returns a dataframe with mean +/- confidence intervals
`xgx_dirs2char()`	Append filenames to bottom of the plot
`xgx_geom_ci()`	Plot data with mean and confidence intervals
`xgx_geom_pi()`	Plot data with median and percent intervals
`xgx_labels_log10()`	Nice labels for log10.
`xgx_minor_breaks_log10()`	Sets the default minor_breaks for log10 scales
`xgx_plot()`	Create a new xgx plot
`xgx_save()`	Saving plot, automatically annotating the status and denoting the filenames
`xgx_save_table()`	Saving table as an image, also labeling the program that created the table and where the table is stored
`xgx_scale_x_log10()`	log10 scales the x axis with a "pretty" set of breaks
`xgx_scale_x_reverselog10()`	Reverse-log transform for the x scale.
`xgx_scale_x_time_units()` `xgx_scale_y_time_units()`	Convert time units for plotting
`xgx_scale_y_log10()`	log10 scales the y axis with a "pretty" set of breaks
`xgx_scale_y_percentchangelog10()` `xgx_scale_x_percentchangelog10()`	percentchangelog10 transform for the y scale.
`xgx_scale_y_reverselog10()`	Reverselog transform for the y scale.
`xgx_stat_ci()`	Plot data with mean and confidence intervals
`xgx_stat_pi()`	Plot data with median and percent intervals
`xgx_stat_smooth()` `xgx_geom_smooth()` `xgx_geom_smooth_emax()`	Wrapper for stat_smooth
`xgx_summarize_covariates()`	Summarize Covariate information in a dataset
`xgx_summarize_data()`	Check data for various issues
`xgx_theme()`	Calls the standard theme for xGx graphics
`xgx_theme_set()`	Sets the standard theme for xGx graphics

Reference

All functions