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

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Documentation for package ‘mvMonitoring’ version 0.2.4

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

mvMonitoring-package	A Package for Multivariate Statistical 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 Multi-State Process
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 Process
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