Package: cvCovEst 1.2.2

cvCovEst: Cross-Validated Covariance Matrix Estimation

An efficient cross-validated approach for covariance matrix estimation, particularly useful in high-dimensional settings. This method relies upon the theory of high-dimensional loss-based covariance matrix estimator selection developed by Boileau et al. (2022) <doi:10.1080/10618600.2022.2110883> to identify the optimal estimator from among a prespecified set of candidates.

Authors:Philippe Boileau [aut, cre, cph], Nima Hejazi [aut], Brian Collica [aut], Jamarcus Liu [ctb], Mark van der Laan [ctb, ths], Sandrine Dudoit [ctb, ths]

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cvCovEst.pdf |cvCovEst.html✨
cvCovEst/json (API)
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Peer review:

Bug tracker:https://github.com/philboileau/cvcovest/issues

On CRAN:

covariance-matrix-estimationcross-validationhigh-dimensional-statisticsnonparametric-statistics

20 exports 13 stars 2.28 score 83 dependencies 2 dependents 27 scripts 437 downloads

Last updated 7 months agofrom:f6ef42b32e. Checks:OK: 7. Indexed: yes.

Exports:adaptiveLassoEstbandingEstcvCovEstcvFrobeniusLosscvMatrixFrobeniusLosscvScaledMatrixFrobeniusLossdenseLinearShrinkEstis.cvCovEstlinearShrinkEstlinearShrinkLWEstnlShrinkLWEstpoetEstrobustPoetEstsampleCovEstscadEstspikedFrobeniusShrinkEstspikedOperatorShrinkEstspikedSteinShrinkEsttaperingEstthresholdingEst

Dependencies:abindassertthatbackportsbootbroomcarcarDataclicodetoolscolorspacecoopcorrplotcowplotcpp11data.tableDerivdigestdoBydplyrfansifarverfuturefuture.applygenericsggplot2ggpubrggrepelggsciggsignifglobalsgluegridExtragtableisobandlabelinglatticelifecyclelistenvlme4magrittrMASSMatrixMatrixModelsmatrixStatsmgcvmicrobenchmarkminqamodelrmunsellnlmenloptrnnetnumDerivorigamiparallellypbkrtestpillarpkgconfigpolynompurrrquantregR6rbibutilsRColorBrewerRcppRcppEigenRdpackrlangRMTstatRSpectrarstatixscalesSparseMstringistringrsurvivaltibbletidyrtidyselectutf8vctrsviridisLitewithr