Package: FPCdpca 0.1.0

FPCdpca: The FPCdpca Criterion on Distributed Principal Component Analysis

We consider optimal subset selection in the setting that one needs to use only one data subset to represent the whole data set with minimum information loss, and devise a novel intersection-based criterion on selecting optimal subset, called as the FPC criterion, to handle with the optimal sub-estimator in distributed principal component analysis; That is, the FPCdpca. The philosophy of the package is described in Guo G. (2020) <doi:10.1007/s00180-020-00974-4>.

Authors:Guangbao Guo [aut, cre, cph], Jiarui Li [ctb]

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FPCdpca.pdf |FPCdpca.html✨
FPCdpca/json (API)

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7 exports 0.09 score 72 dependencies 177 downloads

Last updated 4 months agofrom:033270ac6f. Checks:OK: 7. Indexed: yes.

Exports:DepcaDpcaDrpDrpcaDrsvdDsvdFPC

Dependencies:ADMMbase64encbitbit64bslibcachemclarabelcliclustercodetoolsCVXRdbscandigestdoParallelECOSolveRevaluatefastclusterfastmapfontawesomeforeachfsgenericsgluegmphighrhtmltoolshtmlwidgetsiteratorsjquerylibjsonliteknitrlabdsvlatticelifecyclemagrittrmaotaiMASSMatrixmatrixcalcmclustcompmemoisemgcvmimeminpack.lmnlmeosqppracmaR6RANNrappdirsrbibutilsRcppRcppArmadilloRcppDERcppDistRcppEigenRdimtoolsRdpackrglrlangrmarkdownRmpfrRSpectrarsvdRtsnesassscatterplot3dscsshapestinytexxfunyaml