Package: viraldomain 0.0.6.9000

viraldomain: Applicability Domain Methods of Viral Load and CD4 Lymphocytes

Provides methods for assessing the applicability domain of models that predict viral load and CD4 (Cluster of Differentiation 4) lymphocyte counts. These methods help determine the extent of extrapolation when making predictions.

Authors:Juan Pablo Acuña González [aut, cre]

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viraldomain.pdf |viraldomain.html
viraldomain/json (API)
NEWS

# Install 'viraldomain' in R:
install.packages('viraldomain', repos = c('https://juanv66x.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/juanv66x/viraldomain/issues

Datasets:
  • sero - Seropositive Data for Applicability Domain Testing
  • viral - Predictive Modeling Data for Viral Load and CD4 Lymphocyte Counts

On CRAN:

applicability-domaincd4-lymphocytesviral-load

3.23 score 17 scripts 182 downloads 6 exports 73 dependencies

Last updated 3 months agofrom:3ee490ab99. Checks:7 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKJan 15 2025
R-4.5-winOKJan 15 2025
R-4.5-linuxOKJan 15 2025
R-4.4-winOKJan 15 2025
R-4.4-macOKJan 15 2025
R-4.3-winOKJan 15 2025
R-4.3-macOKJan 15 2025

Exports:knn_domain_scoremars_domain_scorenn_domain_scorenormalized_domain_plotrf_domain_scoresimple_domain_plot

Dependencies:applicableclasscliclockcodetoolscolorspacecpp11data.tablediagramdigestdplyrfansifarverfuturefuture.applygenericsggplot2globalsgluegowergtablehardhatipredisobandKernSmoothlabelinglatticelavalifecyclelistenvlubridatemagrittrMASSMatrixmgcvmodelenvmunsellnlmennetnumDerivparallellyparsnippillarpkgconfigprettyunitsprodlimprogressrproxyCpurrrR6RColorBrewerRcppRcppArmadillorecipesrlangrpartscalesshapeSQUAREMstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetzdbutf8vctrsviridisLitewithrworkflows