Man pages for mvMonitoring
Multi-State Adaptive Dynamic Principal Component Analysis for Multivariate Process Monitoring
| dataStateSwitch | Alternate Observations in a Data Frame over States |
| fault1A_xts | Process Data under a System Shift Fault |
| fault2A_xts | Process Data under a System Drift Fault |
| fault3A_xts | Process Data under a System Signal Amplification |
| faultDetect | Process Fault Detection |
| faultFilter | Process Fault Filtering |
| faultSwitch | Induce the Specified Fault on NOC Observations |
| mspContributionPlot | Contribution Plots |
| mspMonitor | Real-Time Process Monitoring Function |
| mspProcessData | Simulate Normal or Fault Observations from a Single-State or... |
| mspSPEPlot | Squared Prediction Error Contribution Plots |
| mspSubset | Multi-State Subsetting |
| mspT2Plot | T-Squared Contribution Plots |
| mspTrain | Multi-State Adaptive-Dynamic Process Training |
| mspWarning | Process Alarms |
| mvMonitoring | A Package for Multivariate Statistical Process Monitoring |
| normal_switch_xts | Process Data under Normal Conditions |
| oneDay_clean | Real Process Data for Testing |
| pca | PCA for Data Scatter Matrix |
| processMonitor | Adaptive Process Training |
| processNOCdata | Simulate NOC Observations from a Single-State or Multi-State... |
| quantile.density | Extract Quantiles from 'density' Objects |
| rotate3D | Three-Dimensional Rotation Matrix |
| rotateScale3D | Three-Dimensional Rotation and Scaling Matrix |
| tenDay_clean | Real Process Data for Training |
| threshold | Non-parametric Threshold Estimation |
