Package: MERO 0.1.2

MERO: Performing Monte Carlo Expectation Maximization Random Forest Imputation for Biological Data

Perform missing value imputation for biological data using the random forest algorithm, the imputation aim to keep the original mean and standard deviation consistent after imputation.

Authors:Mohamed Soudy [aut, cre]

MERO_0.1.2.tar.gz
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MERO_0.1.2.tgz(r-4.4-any)MERO_0.1.2.tgz(r-4.3-any)
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MERO.pdf |MERO.html✨
MERO/json (API)

Peer review:

On CRAN:

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

4 exports 0.00 score 81 dependencies 2 scripts 290 downloads

Last updated 2 years agofrom:4988b8ecf7. Checks:OK: 7. Indexed: yes.

Exports:EvalImpMEROPlotCorrelateMeanRMSE

Dependencies:abindbackportsbootbroomcarcarDataclicodetoolscolorspacecorrplotcowplotcpp11crayonDerivdigestdoBydoParalleldoRNGdplyrfansifarverforeachgenericsggplot2ggpubrggrepelggsciggsignifgluegridExtragtablehmsisobanditeratorsitertoolslabelinglatticelifecyclelme4magrittrMASSMatrixMatrixModelsmgcvmicrobenchmarkminqamissForestmodelrmunsellnlmenloptrnnetnumDerivpbkrtestpillarpkgconfigpolynomprettyunitsprogresspurrrquantregR6randomForestRColorBrewerRcppRcppEigenrlangrngtoolsrstatixscalesSparseMstringistringrsurvivaltibbletidyrtidyselectutf8vctrsviridisLitewithr