Crandore Hub

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.

Versions across snapshots

VersionRepositoryFileSize
2.0.1 rolling linux/jammy R-4.5 ssMRCD_2.0.1.tar.gz 1.2 MiB
2.0.1 rolling linux/noble R-4.5 ssMRCD_2.0.1.tar.gz 1.2 MiB
2.0.1 rolling source/ R- ssMRCD_2.0.1.tar.gz 863.1 KiB
2.0.1 latest linux/jammy R-4.5 ssMRCD_2.0.1.tar.gz 1.2 MiB
2.0.1 latest linux/noble R-4.5 ssMRCD_2.0.1.tar.gz 1.2 MiB
2.0.1 latest source/ R- ssMRCD_2.0.1.tar.gz 863.1 KiB
2.0.1 2026-04-26 source/ R- ssMRCD_2.0.1.tar.gz 863.1 KiB
2.0.1 2026-04-23 source/ R- ssMRCD_2.0.1.tar.gz 863.1 KiB
2.0.1 2026-04-09 windows/windows R-4.5 ssMRCD_2.0.1.zip 1.5 MiB
1.1.0 2025-04-20 source/ R- ssMRCD_1.1.0.tar.gz 575.1 KiB

Dependencies (latest)

Imports

LinkingTo

Suggests