mvMonitoring

Multi-State Adaptive Dynamic Principal Component Analysis for Multivariate Process Monitoring

CRAN Package

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 , 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


Insights

Last 30 days

Last 365 days

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Data provided by CRAN


Binaries


Dependencies

  • Depends1 package
  • Imports9 packages
  • Suggests3 packages