RobustEM: Robust Mixture Modeling Fitted via Spatial-EM Algorithm for
Model-Based Clustering and Outlier Detection
The Spatial-EM is a new robust EM algorithm for the finite
mixture learning procedures. The algorithm utilizes median-
based location and rank-based scatter estimators to replace sample
mean and sample covariance matrix in each M step, hence enhancing
stability and robustness of the algorithm. To understand more about
this algorithm, read the article
”Yu, K., Dang, X., Bart Jr, H. and Chen, Y. (2015). Robust Model-
based Learning via Spatial-EM Algorithm. IEEE Transactions on
Knowledge and Data Engineering, 27(6), 1670-1682.
doi:10.1109/TKDE.2014.2373355”.
| Version: |
1.0 |
| Depends: |
R (≥ 2.15.0) |
| Imports: |
mvtnorm, e1071, ggplot2, ellipse, doParallel, grid, foreach |
| Published: |
2015-06-05 |
| Author: |
Aishat Aloba, Kai Yu, Xin Dang, Yixin Chen, and Henry Bart Jr. |
| Maintainer: |
Aishat Aloba <adetokaloba at gmail.com> |
| License: |
GPL-3 |
| NeedsCompilation: |
yes |
| CRAN checks: |
RobustEM results |
Downloads: