Package: sGMRFmix 0.3.0

sGMRFmix: Sparse Gaussian Markov Random Field Mixtures for Anomaly Detection

An implementation of sparse Gaussian Markov random field mixtures presented by Ide et al. (2016) <doi:10.1109/ICDM.2016.0119>. It provides a novel anomaly detection method for multivariate noisy sensor data. It can automatically handle multiple operational modes. And it can also compute variable-wise anomaly scores.

Authors:Koji Makiyama [cre, aut]

sGMRFmix_0.3.0.tar.gz
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sGMRFmix.pdf |sGMRFmix.html
sGMRFmix/json (API)
NEWS

# Install 'sGMRFmix' in R:
install.packages('sGMRFmix', repos = c('https://hoxo-m.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

On CRAN:

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

2.34 score 1 stars 22 scripts 161 downloads 6 exports 39 dependencies

Last updated 7 years agofrom:4bf36707cf. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 20 2024
R-4.5-winOKNov 20 2024
R-4.5-linuxOKNov 20 2024
R-4.4-winOKNov 20 2024
R-4.4-macOKNov 20 2024
R-4.3-winOKNov 20 2024
R-4.3-macOKNov 20 2024

Exports:compute_anomaly_scoregenerate_test_datagenerate_test_labelsgenerate_train_dataplot_multivariate_datasGMRFmix

Dependencies:clicolorspacecpp11dplyrfansifarvergenericsggplot2glassogluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellmvtnormnlmepillarpkgconfigpurrrR6RColorBrewerrlangscalesstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithrzoo

Sparse Gaussian MRF Mixtures for Anomaly Detection

Rendered fromsGMRFmix.Rmdusingknitr::rmarkdownon Nov 20 2024.

Last update: 2018-04-16
Started: 2018-02-28

Readme and manuals

Help Manual

Help pageTopics
Compute anomaly scorescompute_anomaly_score
Generate test datagenerate_test_data
Generate test labelsgenerate_test_labels
Generate train datagenerate_train_data
Plot multivariate dataplot_multivariate_data
Sparse Gaussian Markov Random Field MixturessGMRFmix