tidyvpc: VPC Percentiles and Prediction Intervals (original) (raw)
Perform a Visual Predictive Check (VPC), while accounting for stratification, censoring, and prediction correction. Using piping from 'magrittr', the intuitive syntax gives users a flexible and powerful method to generate VPCs using both traditional binning and a new binless approach Jamsen et al. (2018) <doi:10.1002/psp4.12319> with Additive Quantile Regression (AQR) and Locally Estimated Scatterplot Smoothing (LOESS) prediction correction.
Version:
1.5.2
Depends:
R (≥ 3.5.0)
Imports:
data.table (≥ 1.9.8), magrittr, quantreg (≥ 5.51), rlang (≥ 0.3.0), methods, mgcv, classInt, cluster, ggplot2, stats, fastDummies, utils, egg
Suggests:
dplyr, KernSmooth, knitr, R.rsp, nlmixr2, shiny, remotes, vpc, rmarkdown, testthat (≥ 2.1.0), vdiffr (≥ 1.0.0)
Published:
2024-11-21
DOI:
Author:
Olivier Barriere [aut], Benjamin Rich [aut], James Craig 
[aut, cre], Samer Mouksassi [aut], Bill Denney [ctb], Michael Tomashevskiy [ctb], Kris Jamsen [ctb], Certara USA, Inc. [cph, fnd]
Maintainer:
James Craig <james.craig at certara.com>
BugReports:
https://github.com/certara/tidyvpc/issues
License:
MIT + file
URL:
https://github.com/certara/tidyvpc
NeedsCompilation:
no
Materials:
In views:
CRAN checks: