Package index • Model-Independent Variable Selection with Variable Priority

All functions
`alzheimers`	Alzheimer's Disease Dataset
`cv.varpro()`	Cross-Validated Cutoff Value for Variable Priority (VarPro)
`glioma`	Diffuse Adult Glioma
`hrrecov`	Exercise Heart Rate Recovery and Mortality
`importance()`	Calculate Importance for VarPro and UVarPro Objects
`isopro()`	Identify Anomalous Data
`ivarpro()`	Individual Variable Priority (iVarPro): Case-Specific Variable Importance
`outpro()` `outpro.null()`	Model and subsapce aware out-of-distribution (OOD) scoring with outPro
`partialpro()`	Partial Effects for Variable(s)
`plot(<ivarpro>)`	Plot iVarPro Gradients for a Single Variable
`plot(<partialpro>)`	Plot method for partialpro objects
`predict(<isopro>)`	Prediction for Isopro for Identifying Anomalous Data
`predict(<ivarpro>)`	Predict iVarPro Gradients on New Data
`predict(<uvarpro>)`	Prediction on Test Data using Unsupervised VarPro
`predict(<varpro>)`	Prediction on Test Data using VarPro
`uvarpro()`	Unsupervised Variable Selection using Variable Priority (UVarPro)
`varpro()`	Model-Independent Variable Selection via the Rule-based Variable Priority (VarPro)
`varpro.news()`	Show the NEWS file
`varpro.strength()`	Obtain Strength Array and Other Values from a VarPro Object

Reference