Package: packMBPLSDA 0.9.0

Marion Brandolini-Bunlon

packMBPLSDA: Multi-Block Partial Least Squares Discriminant Analysis

Several functions are provided to implement a MBPLSDA : components search, optimal model components number search, optimal model validity test by permutation tests, observed values evaluation of optimal model parameters and predicted categories, bootstrap values evaluation of optimal model parameters and predicted cross-validated categories. The use of this package is described in Brandolini-Bunlon et al (2019. Multi-block PLS discriminant analysis for the joint analysis of metabolomic and epidemiological data. Metabolomics, 15(10):134).

Authors:Marion Brandolini-Bunlon, Stephanie Bougeard, Melanie Petera, Estelle Pujos-Guillot

packMBPLSDA_0.9.0.tar.gz
packMBPLSDA_0.9.0.tar.gz(r-4.5-noble)packMBPLSDA_0.9.0.tar.gz(r-4.4-noble)
packMBPLSDA_0.9.0.tgz(r-4.4-emscripten)packMBPLSDA_0.9.0.tgz(r-4.3-emscripten)
packMBPLSDA.pdf |packMBPLSDA.html
packMBPLSDA/json (API)

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

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

1.00 score 3 scripts 160 downloads 12 exports 109 dependencies

Last updated 2 years agofrom:a236b18f67. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 08 2024
R-4.5-linuxOKNov 08 2024

Exports:boot_mbplsdacvpred_mbplsdadisjunctivembplsdapermut_mbplsdaplot_boot_mbplsdaplot_cvpred_mbplsdaplot_permut_mbplsdaplot_pred_mbplsdaplot_testdim_mbplsdapred_mbplsdatestdim_mbplsda

Dependencies:abindade4backportsbase64encbootbroombslibcachemcarcarDatacliclustercodetoolscolorspacecowplotcpp11crosstalkDerivdigestdoBydoParalleldplyrDTellipseemmeansestimabilityevaluateFactoMineRfansifarverfastmapflashClustfontawesomeforeachFormulafsgenericsggplot2ggrepelgluegtablehighrhtmltoolshtmlwidgetshttpuvisobanditeratorsjquerylibjsonliteknitrlabelinglaterlatticelazyevalleapslifecyclelme4magrittrMASSMatrixMatrixModelsmemoisemgcvmicrobenchmarkmimeminqamodelrmultcompViewmunsellmvtnormnlmenloptrnnetnumDerivpbkrtestpillarpixmappkgconfigplyrpROCpromisespurrrquantregR6rappdirsRColorBrewerRcppRcppArmadilloRcppEigenrlangrmarkdownsassscalesscatterplot3dspSparseMstringistringrsurvivaltibbletidyrtidyselecttinytexutf8vctrsviridisLitewithrxfunyaml