Package index • xpose.xtras

xp_xtras objects

Functions for creating, checking and manipulating xp_xtras objects.

as_xpdb_x() as_xp_xtras() check_xpdb_x() check_xp_xtras(): Convert an object to an xpose_data and xp_xtras object
check_xpose_set() check_xpose_set_item(): Check an xpose_set object
is_xp_xtras(): Basic class checker for xp_xtras
set_var_levels(): Set variable levels
set_var_types() experimental: Set variable types
set_var_types(<default>) experimental: Set variable types
set_var_types(<xp_xtras>) experimental: Set variable types
set_var_types_x() experimental: Set variable types
as_leveler() is_leveler() lvl_bin() lvl_sex() lvl_inord(): Level-defining helper functions
val2lvl(): Translate values to levels
backfill_iofv(): Add individual objective function to data
xp_var(): xp_var Method
check_levels(): Verify validity of level list

xpose sets

Work with collections of models using xpose_set.

xpose_set(): Generate a set of xpdb objects
xset_lineage(): Determine lineage within a set
xset_waterfall(): Waterfall plot
add_xpdb(): Add one or more xpdb objects to an xpose_set
focus_xpdb() unfocus_xpdb() focused_xpdbs() focus_function() focus_qapply(): Focus on an xpdb object in an xpose_set
reshape_set() unreshape_set(): Convert xpose_set to a nested list.
diagram_lineage() experimental: Visualize xpose_set
add_prm_association() drop_prm_association(): Describe parameter associations
add_cov_association() drop_cov_association(): Describe parameter/covariate associations
mutate_prm(): Transform parameter values in place
add_relationship() remove_relationship(): Add relationship(s) to an xpose_set
`%p%`: Binary check if LHS is parent of RHS
logLik(<xpose_set>) AIC(<xpose_set>) BIC(<xpose_set>) experimental: Log-likelihood, AIC and BIC across an xpose_set

Plotting helpers

Additional plotting functions and themes extending xpose.

xplot_binned(): Generic binned trend plotting function
xplot_boxplot(): Default xpose boxplot function
xplot_forest(): Default xpose forest plot function
xplot_heatmap(): Generic heatmap plotting function
xplot_pairs(): Wrapper around ggpairs
xplot_rocplot(): Default xpose ROC plot function
iofv_vs_mod(): Objective function changes across models
prm_waterfall() eta_waterfall() iofv_waterfall(): Specific waterfall plots
shark_plot() dofv_vs_id(): Individual contributions to dOFV
prm_contcov() prm_catcov() prm_cov(): Continuous/categorical covariate effect tables
eta_vs_catcov(): Eta categorical covariate plots (typical)
eta_vs_contcov(): Eta continuous covariate plots (typical)
eta_grid() cov_grid() eta_vs_cov_grid(): Grid plots
dv_vs_ipred_modavg() dv_vs_pred_modavg() ipred_vs_idv_modavg() pred_vs_idv_modavg() plotfun_modavg() experimental: Model average plots
ipred_vs_ipred() pred_vs_pred(): Compare model predictions
catdv_vs_dvprobs(): Non-simulation based likelihood model diagnostic
catdv_vs_ipred(): Binned calibration plot for categorical DVs
catdv_vs_occ(): Longitudinal binned observed vs. predicted plot for categorical DVs
roc_by_mod(): ROC curve across models
roc_plot(): ROC Plot for categorical DVs
shark_colors(): Change colors of shark plots
shk_grid() shk_vs_cov_grid(): Shrinkage contribution grid plots
shk_vs_catcov(): Shrinkage contribution versus categorical covariates
shk_vs_contcov(): Shrinkage contribution versus continuous covariates
normalize_etas() normalise_etas(): Normalize etas by their omega- or empirical-SD-implied scale
ind_roc(): Individual ROC plots
ind_plots_sample(): Individual plots for a (stratified) sample of individuals
xset_waterfall(): Waterfall plot
cormat(): Parameter correlation/covariance matrix heatmap
xp_xtra_theme(): Extra theme defaults
xp4_xtra_theme(): Updated version of the xpose4 theme
grab_xpose_plot(): Grab processed xpose_plot
wrap_xp_ggally(): Ensure consistent style with GGally functions

Plot output & session options

Default labels, watermarks, saving, batch plotting, and the xpose.xtras.* option family.

apply_default_labs(): Apply default label overrides to a plot
set_default_labs(): Set default plot label overrides on an xp_xtras object
add_watermark(): Add a watermark to a plot
set_default_watermark(): Set default watermark options on an xp_xtras object
ggsave_xp(): Save a plot with xpose.xtras default output resolution
plot(<xpose_data>): Generate a batch of diagnostic plots from an xpdb
set_default_plots(): Set a default plot spec on an xp_xtras object
set_xtras_options(): Set xpose.xtras session options
get_xtras_option(): Inspect which xpose.xtras option value is dominant

Utilities

Miscellaneous helpers and integrations.

modavg_xpdb() experimental: Create a model-averaged xpose data object
cov_forest(): Covariate effect forest plot
eta_grid() cov_grid() eta_vs_cov_grid(): Grid plots
attach_nlmixr2(): Attach nlmixr2 fit object to xpose data object
backfill_nlmixr2_props(): Populate some properties from nlmixr2 fit
get_prm_nlmixr2(): get_prm equivalent for nlmixr2 fits
nlmixr2_as_xtra(): Convenience function for ingesting an nlmixr2 model to xpose and xpose.xtras
nlmixr2_prm_associations(): Based on associations baked into nlmixr2, automatically add to xpose data
nlmixr_example() nlmixr2_example(): Generate example xp_xtras objects from nlmixr2 fits
desc_from_comments(): Backfill utility for descriptions
edit_xpose_data(): Master xpdb editing function
expose_param(): Expose a model parameter of xpdb objects in an xpose_set
expose_property(): Expose a property of xpdb objects in an xpose_set
get_prop(): Generic function to extract a property from a model summary
set_prop(): Set a summary property
get_index() set_index(): Get full index for xpose_data data
set_base_model() get_base_model() unset_base_model(): Base model for xpose_set
set_dv_probs(): Set probability columns for categorical endpoints
list_dv_probs(): For a categorical DV variable, show associated probabilities
group_by_x() ungroup_x(): Group/ungroup and summarize variables in an xpdb
mutate_x() rename_x(): Add, remove or rename variables in an xpdb
left_join_x() left_join(<xpose_data>) experimental: Backfill missing variables via a left join
select_subset(): Convenience wrapper for tidyselect
set_option(): Set an xpose option
reportable_digits(): Reportable digits for model fit
test_xpdb(): Logical instead of exception for xpose data check
irep(): Add simulation counter
patch_condn() experimental: Patch condition number extraction
derive_prm() backfill_derived(): Derive full parameter set for mammillary PK model
derive_shk() backfill_shk(): Derive per-individual contribution to eta shrinkage
recalc_shk(): Recalculate eta shrinkage from individual estimates
diagnose_constants(): Check for potential parameterization issues
get_prm(): Access model parameters
get_shk(): Get shrinkage estimates from model summary
get_cov_matrix(): Extract a parameter covariance or correlation matrix
list_vars(): Updates to list_vars
xp_from_bbr(): Convenience function for ingesting a bbr model into xpose and xpose.xtras
xtras_data(): Read model outputs directly into an xp_xtras object
logLik(<xpose_data>) experimental: Log-likelihood, AIC and BIC for xpose_data objects
add_process_preset() process_preset() print_process_preset() remove_process_preset() amend_process_preset() experimental: Add, apply, list, amend or remove xpdb processing presets
persist_process_presets(): Write current process presets out to a .Rprofile

Data

Example objects for documentation.

pheno_base: An xp_xtras example of a base model
pheno_final: An xp_xtras example of a final model
pheno_saem: An xp_xtras example of a final model
pheno_set: A more complex example of xpose_set object
pkpd_m3: An xp_xtras example of an M3 model
pkpd_m3_df: An xp_xtras example of an M3 model (dataset)
vismo_dtmm: An xp_xtras example of the discrete-time Markov model of categorical vismodegib data
vismo_pomod: An xp_xtras example of the proportional odds categorical vismodegib model
vismodegib: A tibble of mock data used for fitting vismodegib models
xpdb_set: An example xpose_set object
xpdb_x: An example xp_xtras object