Use multi-state splitting to apply Adaptive-Dynamic PCA (ADPCA) to data generated from a continuous-time multivariate industrial or natural process. Employ PCA-based dimension reduction to extract linear combinations of relevant features, reducing computational burdens. For a description of ADPCA, see <doi:10.1007/s00477-016-1246-2>, the 2016 paper from Kazor et al. The multi-state application of ADPCA is from a manuscript under current revision entitled "Multi-State Multivariate Statistical Process Control" by Odom, Newhart, Cath, and Hering, and is expected to appear in Q1 of 2018.
| Version: | 0.1.0 |
| Depends: | R (≥ 2.10) |
| Imports: | BMS, dplyr, lazyeval, plyr, rlang, utils, xts, zoo, robustbase, graphics |
| Suggests: | knitr, rmarkdown |
| Published: | 2017-10-20 |
| Author: | Melissa Johnson [aut], Gabriel Odom [aut, cre], Ben Barnard [aut], Karen Kazor [aut], Amanda Hering [aut] |
| Maintainer: | Gabriel Odom <gabriel.odom at med.miami.edu> |
| License: | GPL-2 |
| URL: | https://github.com/gabrielodom/mvMonitoring |
| NeedsCompilation: | no |
| CRAN checks: | mvMonitoring results |
| Reference manual: | mvMonitoring.pdf |
| Vignettes: |
Workflow |
| Package source: | mvMonitoring_0.1.0.tar.gz |
| Windows binaries: | r-devel: mvMonitoring_0.1.0.zip, r-release: mvMonitoring_0.1.0.zip, r-oldrel: mvMonitoring_0.1.0.zip |
| macOS binaries: | r-release: mvMonitoring_0.1.0.tgz, r-oldrel: mvMonitoring_0.1.0.tgz |
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