mvMonitoring
Multi-State Adaptive Dynamic Principal Component Analysis for Multivariate Process Monitoring
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.
- Version0.2.4
- R version≥ 2.10
- LicenseGPL-2
- Needs compilation?No
- Last release11/21/2023
Documentation
Team
Gabriel Odom
MaintainerShow author detailsBen Barnard
Show author detailsRolesAuthorMelissa Innerst
Show author detailsRolesAuthorKaren Kazor
Show author detailsRolesAuthorAmanda Hering
Show author detailsRolesAuthor
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- Imports7 packages
- Suggests3 packages