Package: SCOUTer 1.0.0

Alba Gonzalez Cebrian

SCOUTer: Simulate Controlled Outliers

Using principal component analysis as a base model, 'SCOUTer' offers a new approach to simulate outliers in a simple and precise way. The user can generate new observations defining them by a pair of well-known statistics: the Squared Prediction Error (SPE) and the Hotelling's T^2 (T^2) statistics. Just by introducing the target values of the SPE and T^2, 'SCOUTer' returns a new set of observations with the desired target properties. Authors: Alba González, Abel Folch-Fortuny, Francisco Arteaga and Alberto Ferrer (2020).

Authors:Alba Gonzalez Cebrian [aut, cre], Abel Folch-Fortuny [aut], Francisco Arteaga [aut], Alberto Ferrer [aut]

SCOUTer_1.0.0.tar.gz
SCOUTer_1.0.0.tar.gz(r-4.5-noble)SCOUTer_1.0.0.tar.gz(r-4.4-noble)
SCOUTer_1.0.0.tgz(r-4.4-emscripten)SCOUTer_1.0.0.tgz(r-4.3-emscripten)
SCOUTer.pdf |SCOUTer.html✨
SCOUTer/json (API)

Peer review:

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

18 exports 0.00 score 67 dependencies 2 scripts 181 downloads

Last updated 4 years agofrom:e19a07eb39. Checks:OK: 2. Indexed: yes.

Exports:barwithuclcustombardistplotdistplotsimpledotagdscplotht2infoobscontribpanelpcamb_classicpcamescoreplotscoreplotsimplescoutscoutgridscoutsimplescoutstepsspeinfoxshift

Dependencies:abindbackportsbootbroomcarcarDataclicolorspacecorrplotcowplotcpp11DerivdoBydplyrfansifarvergenericsggplot2ggpubrggrepelggsciggsignifgluegridExtragtableisobandlabelinglatticelifecyclelme4magrittrMASSMatrixMatrixModelsmgcvmicrobenchmarkminqamodelrmunsellnlmenloptrnnetnumDerivpbkrtestpillarpkgconfigpolynompurrrquantregR6RColorBrewerRcppRcppEigenrlangrstatixscalesSparseMstringistringrsurvivaltibbletidyrtidyselectutf8vctrsviridisLitewithr