Package: nlmeVPC 2.6

nlmeVPC: Visual Model Checking for Nonlinear Mixed Effect Model

Various visual and numerical diagnosis methods for the nonlinear mixed effect model, including visual predictive checks, numerical predictive checks, and coverage plots (Karlsson and Holford, 2008, <https://www.page-meeting.org/?abstract=1434>).

Authors:Eun-Kyung Lee [aut, cre], Eun-Hwa Kang [aut]

nlmeVPC_2.6.tar.gz
nlmeVPC_2.6.zip(r-4.5)nlmeVPC_2.6.zip(r-4.4)nlmeVPC_2.6.zip(r-4.3)
nlmeVPC_2.6.tgz(r-4.4-x86_64)nlmeVPC_2.6.tgz(r-4.4-arm64)nlmeVPC_2.6.tgz(r-4.3-x86_64)nlmeVPC_2.6.tgz(r-4.3-arm64)
nlmeVPC_2.6.tar.gz(r-4.5-noble)nlmeVPC_2.6.tar.gz(r-4.4-noble)
nlmeVPC_2.6.tgz(r-4.4-emscripten)nlmeVPC_2.6.tgz(r-4.3-emscripten)
nlmeVPC.pdf |nlmeVPC.html
nlmeVPC/json (API)

# Install 'nlmeVPC' in R:
install.packages('nlmeVPC', repos = c('https://ek-lee.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:
  • origdata - Pharmacokinetics of Theophylline with a different schedule of time.
  • simdata - Simulation data

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

14 exports 0.00 score 76 dependencies 11 scripts 282 downloads

Last updated 2 years agofrom:43f02a4aa9. Checks:OK: 1 NOTE: 8. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 09 2024
R-4.5-win-x86_64NOTESep 09 2024
R-4.5-linux-x86_64NOTESep 09 2024
R-4.4-win-x86_64NOTESep 09 2024
R-4.4-mac-x86_64NOTESep 09 2024
R-4.4-mac-aarch64NOTESep 09 2024
R-4.3-win-x86_64NOTESep 09 2024
R-4.3-mac-x86_64NOTESep 09 2024
R-4.3-mac-aarch64NOTESep 09 2024

Exports:aqrVPCasVPCbootVPCcoverageDetailplotcoverageplotFindBestCutfindQuantilefindSIMQfindSIMQuantilemakeCOVbinNumericalCheckoptKquantVPCVPCgraph

Dependencies:backportsbase64encbslibcachemcheckmatecliclustercolorspacedata.tabledigestevaluatefansifarverfastmapfontawesomeforeignFormulafsggplot2gluegridExtragtablehighrHmischtmlTablehtmltoolshtmlwidgetsisobandjquerylibjsonliteknitrlabelinglatticelifecyclemagrittrMASSMatrixMatrixModelsmemoisemgcvmimemunsellnlmenloptrnnetnumDerivoptimxpillarpkgconfigpracmaquantregR6rappdirsRColorBrewerRcppRcppArmadillorlangrmarkdownrpartrstudioapisassscalesSparseMstringistringrsurvivaltibbletimeDatetinytexutf8vctrsviridisviridisLitewithrxfunyaml