Package: ssMRCD 2.0.1

ssMRCD: Robust Estimators for Multi-Group and Spatial Data

Estimation of robust estimators for multi-group and spatial data including the casewise robust Spatially Smoothed Minimum Regularized Determinant (ssMRCD) estimator and its usage for local outlier detection as described in Puchhammer and Filzmoser (2023) <doi:10.1080/10618600.2023.2277875> as well as for sparse robust PCA for multi-source data described in Puchhammer, Wilms and Filzmoser (2024) <doi:10.48550/arXiv.2407.16299>. Moreover, a cellwise robust multi-group Gaussian mixture model (MG-GMM) is implemented as described in Puchhammer, Wilms and Filzmoser (2024) <doi:10.48550/arXiv.2504.02547>. Included are also complementary visualization and parameter tuning tools.

Authors:Patricia Puchhammer [aut, cre, cph], Peter Filzmoser [aut]

ssMRCD_2.0.1.tar.gz
ssMRCD_2.0.1.zip(r-4.7)ssMRCD_2.0.1.zip(r-4.6)ssMRCD_2.0.1.zip(r-4.5)
ssMRCD_2.0.1.tgz(r-4.6-x86_64)ssMRCD_2.0.1.tgz(r-4.6-arm64)ssMRCD_2.0.1.tgz(r-4.5-x86_64)ssMRCD_2.0.1.tgz(r-4.5-arm64)
ssMRCD_2.0.1.tar.gz(r-4.7-arm64)ssMRCD_2.0.1.tar.gz(r-4.7-x86_64)ssMRCD_2.0.1.tar.gz(r-4.6-arm64)ssMRCD_2.0.1.tar.gz(r-4.6-x86_64)
ssMRCD_2.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
ssMRCD/json (API)

# Install 'ssMRCD' in R:
install.packages('ssMRCD', repos = c('https://patriciapuch.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

Conda:

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

openblascpp

2.78 score 10 scripts 548 downloads 10 exports 80 dependencies

Last updated from:71bacdf712. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK243
linux-devel-x86_64OK255
source / vignettesOK370
linux-release-arm64OK234
linux-release-x86_64OK224
macos-release-arm64OK237
macos-release-x86_64OK356
macos-oldrel-arm64OK257
macos-oldrel-x86_64OK374
windows-develOK214
windows-releaseOK222
windows-oldrelOK225
wasm-releaseOK170

Exports:aligncellMGGMMgeo_weightsgroups_gridbasedlocOutsmsPCAresiduals_mggmmscoresssMRCDtime_weights

Dependencies:askpassbitbit64bootcellrangercellWiseclassclicliprcpp11crayoncurldata.tabledbscanDEoptimRDescToolse1071ellipseExactexpmfarverforcatsfsgenericsggplot2gldgluegridExtragtablehavenhmshttrisobandjsonlitelabelinglatticelifecyclelmommagrittrMASSMatrixmatrixStatsmimemvtnormopensslpcaPPpillarpkgconfigplyrprettyunitsprogressproxyR6RColorBrewerRcppRcppArmadilloreadrreadxlrematchreshape2rlangrobustbaserootSolverrcovrstudioapiS7scalesshapestringistringrsvdsystibbletidyselecttzdbutf8vctrsviridisLitevroomwithr

Cellwise Robust Multi-Group Gaussian Mixture Model
Data Preparation | References
Rendered fromcellMGGMM.Rmdusingknitr::rmarkdown

Last update: 2025-09-11
Started: 2025-09-11

Local Outlier Detection with ssMRCD
Data Preparation | Basic Estimation of ssMRCD with Default Values | Parameter Tuning | Local Outlier Detection | Diagnostics for Local Outlier Detection | 1) Histogramm of Next Distances | References
Rendered fromssMRCD.Rmdusingknitr::rmarkdown

Last update: 2025-09-11
Started: 2023-05-15

Sparse Robust PCA with the ssMRCD Estimator for Multi-Source Data
Data Preparation | Calculating the ssMRCD Estimator for Yearly Groups | Robust Sparse PCA | Hyper-Parameter Tuning | Sparse Robust PCA - Number of PCs | Diagnostic Plots | Loadings | Scores, Score- and Orthogonal-Distances | References
Rendered fromSRPCAMS.Rmdusingknitr::rmarkdown

Last update: 2025-09-11
Started: 2025-09-11