Package: xpose.xtras 0.0.2
John Prybylski
xpose.xtras: Extra Functionality for the 'xpose' Package
Adding some at-present missing functionality, or functions unlikely to be added to the base 'xpose' package. This includes some diagnostic plots that have been missing in translation from 'xpose4', but also some useful features that truly extend the capabilities of what can be done with 'xpose'. These extensions include the concept of a set of 'xpose' objects, and diagnostics for likelihood-based models.
Authors:
xpose.xtras_0.0.2.tar.gz
xpose.xtras_0.0.2.tar.gz(r-4.5-noble)xpose.xtras_0.0.2.tar.gz(r-4.4-noble)
xpose.xtras_0.0.2.tgz(r-4.4-emscripten)xpose.xtras_0.0.2.tgz(r-4.3-emscripten)
xpose.xtras.pdf |xpose.xtras.html✨
xpose.xtras/json (API)
NEWS
| # Install 'xpose.xtras' in R: |
| install.packages('xpose.xtras', repos = 'https://cloud.r-project.org') |
Bug tracker:https://github.com/jprybylski/xpose.xtras/issues2 issues
Pkgdown site:https://jprybylski.github.io
- 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
- 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
Last updated 4 months agofrom:874de11838. Checks:2 OK, 1 NOTE. Indexed: no.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Mar 25 2025 |
| R-4.5-linux | OK | Mar 25 2025 |
| R-4.4-linux | NOTE | Mar 25 2025 |
Exports:%>%%p%add_prm_associationadd_relationshipadd_xpdball_ofany_ofas_leveleras_xp_xtrasas_xpdb_xbackfill_iofvcatdv_vs_dvprobscheck_xp_xtrascheck_xpdb_xcheck_xpose_setcheck_xpose_set_itemcov_griddesc_from_commentsdiagram_lineagedofv_vs_iddrop_prm_associationdv_vs_ipred_modavgdv_vs_pred_modavgedit_xpose_dataeta_grideta_vs_catcoveta_vs_contcoveta_vs_cov_grideta_waterfallexpose_paramexpose_propertyfilterfocus_functionfocus_qapplyfocus_xpdbfocused_xpdbsfranken_propfranken_xpdbget_base_modelget_indexget_prmget_propget_shkgrab_xpose_plotgroup_by_xiofv_vs_modiofv_waterfallipred_vs_idv_modavgipred_vs_ipredirepis_formula_listis_leveleris_xp_xtraslist_dv_probslist_varslvl_binlvl_inordlvl_sexmodavg_xpdbmutatemutate_prmmutate_xplotfun_modavgpred_vs_idv_modavgpred_vs_predprm_waterfallpullremove_relationshiprenamerename_xreportable_digitsreshape_setselectselect_subsetset_base_modelset_dv_probsset_indexset_optionset_propset_var_levelsset_var_typesset_var_types_xshark_colorsshark_plotunfocus_xpdbungroup_xunreshape_setunset_base_modelval2lvlwrap_xp_ggallyxp_xtra_themexp4_xtra_themexplot_boxplotxplot_pairsxpose_setxset_lineagexset_waterfall
Dependencies:assertthatbitbit64cachemclassclassIntclicliprcolorspaceconflictedcpp11crayondplyre1071fansifarverfastmapforcatsgenericsGGallyggforceggplot2ggstatsgluegtablehmsisobandjsonliteKernSmoothlabelinglatticelifecyclemagrittrMASSMatrixmemoisemgcvmunsellnlmepatchworkpillarpkgconfigplyrpmxcvpolyclipprettyunitsprogressproxypurrrR6RColorBrewerRcppRcppEigenreadrrlangscalesstringistringrsurvivalsystemfontstibbletidyrtidyselecttweenrtzdbutf8vctrsviridisLitevpcvroomwithrxpose
The extended xpose data object
Rendered froma01-the-xp_xtra-object.Rmdusingknitr::rmarkdownon Mar 25 2025.Last update: 2024-11-21
Started: 2024-11-21
Useful uncommon plots
Rendered froma03-useful_plots.Rmdusingknitr::rmarkdownon Mar 25 2025.Last update: 2024-11-21
Started: 2024-11-21
Using xpose sets
Rendered froma02-xpose-sets.Rmdusingknitr::rmarkdownon Mar 25 2025.Last update: 2024-11-21
Started: 2024-11-21
Citation
To cite package ‘xpose.xtras’ in publications use:
Prybylski J (2024). xpose.xtras: Extra Functionality for the 'xpose' Package. R package version 0.0.2, https://CRAN.R-project.org/package=xpose.xtras.
Corresponding BibTeX entry:
@Manual{,
title = {xpose.xtras: Extra Functionality for the 'xpose' Package},
author = {John Prybylski},
year = {2024},
note = {R package version 0.0.2},
url = {https://CRAN.R-project.org/package=xpose.xtras},
}
Readme and manuals
xpose.xtras
Introduction
This package adds some extra functionality and plots to the
xpose framework. This
includes some plots that have been missing in translation from
xpose4, but also some
useful features that truly extend the capabilities of what can be done
with xpose.
There are a few bugfixes here and functionality which could easily be
suggested as pull requests to the parent package. Given the size and
broad use of xpose, it appears even minor pull requests take some time
to implement. As such, this package implements those features directly
and if at any point in the future these are added (perhaps in a better
state) to the parent package, they will be deprecated if this package is
in active use.
For those wondering, conflicted is
used to manage bugfix conflicts, so users should be comfortable loading
packages in any order.
Installation
This package is currently only available here, but submission to CRAN is planned soon.
The typical github installation will work.
devtools::install_github("jprybylski/xpose.xtras")
Preview
The grandparent package, xpose4, has a nice collection of figures and
documentation that is referred to as a
“bestiary”. The
documentation site for this package serves as a complete bestiary, but
see the uncommented examples below as a sort of menagerie. There is no
assumption that these examples are self-explanatory, but hopefully users
familiar with xpose will recognize the new (and renewed) tools made
available by this package.
EBEs versus covariates
described <- xpdb_x %>%
set_var_labels(AGE="Age", MED1 = "Digoxin", .problem = 1) %>%
set_var_units(AGE="yrs") %>%
set_var_levels(SEX=lvl_sex(), MED1 = lvl_bin())
eta_vs_contcov(described,etavar=ETA1, quiet=TRUE)
#> `geom_smooth()` using formula = 'y ~ x'
#> `geom_smooth()` using formula = 'y ~ x'
eta_vs_catcov(described,etavar=ETA1, quiet=TRUE)
Shark plots
pheno_set %>%
focus_qapply(backfill_iofv) %>%
dofv_vs_id(run6, run9, quiet = TRUE)
Categorical DVs
pkpd_m3 %>%
set_var_types(catdv=BLQ,dvprobs=LIKE) %>%
set_dv_probs(1, 1~LIKE, .dv_var = BLQ) %>%
set_var_levels(1, BLQ = lvl_bin()) %>%
catdv_vs_dvprobs(quiet=TRUE)
#> `geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'
#> `geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'
