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: 10.32614/CRAN.package.tidyvpc 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 LICENSE URL: https://github.com/certara/tidyvpc NeedsCompilation: no Materials: README NEWS In views: Pharmacokinetics CRAN checks: tidyvpc resultsRetroSearch is an open source project built by @garambo | Open a GitHub Issue
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