Package: mrct 0.0.1.0
Jeremy Oguamalam
mrct: Outlier Detection of Functional Data Based on the Minimum Regularized Covariance Trace Estimator
Detect outlying observations in functional data sets based on the minimum regularized covariance trace (MRCT) estimator. Includes implementation of Oguamalam et al. (2023) <arxiv:2307.13509>.
Authors:
mrct_0.0.1.0.tar.gz
mrct_0.0.1.0.tar.gz(r-4.5-noble)mrct_0.0.1.0.tar.gz(r-4.4-noble)
mrct_0.0.1.0.tgz(r-4.4-emscripten)mrct_0.0.1.0.tgz(r-4.3-emscripten)
mrct.pdf |mrct.html✨
mrct/json (API)
| # Install 'mrct' in R: |
| install.packages('mrct', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 years agofrom:3c8388045d. Checks:2 OK. Indexed: yes.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Feb 23 2025 |
| R-4.5-linux | OK | Feb 23 2025 |
Exports:innerProductmrctmrct.isemrct.plotmrct.rgaussmrct.sparsemrct.sparse.plot
Dependencies:ashbackportsbase64encbitopsbslibcachemcheckmatecliclustercolorspacedata.tableDEoptimRdeSolvedigestevaluatefansifarverfastmapfdafdapacefdsFNNfontawesomeforeignFormulafsggplot2gluegridExtragtablehdrcdehighrHmischtmlTablehtmltoolshtmlwidgetsisobandjquerylibjsonlitekernlabKernSmoothknitrkslabelinglatticelifecyclelocfitmagrittrMASSMatrixmclustmemoisemgcvmimemulticoolmunsellmvtnormnlmennetnumDerivpcaPPpillarpkgconfigplyrpracmaR6rainbowrappdirsrbibutilsRColorBrewerRcppRcppEigenRCurlRdpackreshape2rlangrmarkdownrobustbaserpartrstudioapisassscalesstringistringrtibbletinytexutf8vctrsviridisviridisLitewithrxfunyaml
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Pairwise inner product for L^2 functions | innerProduct |
| Minimum regularized covariance trace estimator | mrct |
| Integrated square error | mrct.ise |
| Plot function for result from 'mrct()' | mrct.plot |
| Random sample from Gaussian process | mrct.rgauss |
| Sparse minimum regularized covariance trace estimator | mrct.sparse |
| Plot function for result from 'mrct.sparse()' | mrct.sparse.plot |