sGMRFmix: Sparse Gaussian Markov Random Field Mixtures for AnomalyDetection
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.
| Version: | 0.3.0 |
| Imports: | ggplot2,glasso,mvtnorm, stats,tidyr, utils,zoo |
| Suggests: | dplyr,ModelMetrics,testthat,covr,knitr,rmarkdown |
| Published: | 2018-04-16 |
| DOI: | 10.32614/CRAN.package.sGMRFmix |
| Author: | Koji Makiyama [cre, aut] |
| Maintainer: | Koji Makiyama <hoxo.smile at gmail.com> |
| License: | MIT + fileLICENSE |
| NeedsCompilation: | no |
| Materials: | NEWS |
| In views: | AnomalyDetection |
| CRAN checks: | sGMRFmix results |
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