_            _    _        _         _
      /\ \         /\ \ /\ \     /\_\      / /\
      \_\ \       /  \ \\ \ \   / / /     / /  \
      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
 / / /      / / /___/ / /     \ \ \ /_/\__/ / /
/_/ /      / / /____\/ /       \ \_\\ \/___/ /
\_\/       \/_________/         \/_/ \_____\/
r-tidyvpc 1.5.2
Propagated dependencies: r-rlang@1.1.6 r-quantreg@6.1 r-mgcv@1.9-3 r-magrittr@2.0.3 r-ggplot2@3.5.2 r-fastdummies@1.7.5 r-egg@0.4.5 r-data-table@1.17.2 r-cluster@2.1.8.1 r-classint@0.4-11
Channel: guix-cran
Location: guix-cran/packages/t.scm (guix-cran packages t)
Home page: https://github.com/certara/tidyvpc
Licenses: Expat
Synopsis: VPC Percentiles and Prediction Intervals
Description:

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.

Total results: 1