Sample Size Calculation for High Dimensional Classification Study
Formula-based PCC of a CV-based classifier
Formula-based method to calculate the PCC of a CV-based classifier whe...
MC simulation-based method to calculate the PCC of a CV-based classifi...
MC simulation-based method to calculate the PCC of a CV-based classifi...
Estimate PCC by DS Method
Alternative HCT Procedure to Choose P-Value Threshold Based on Beta Di...
Original HCT Procedure to Choose P-Value Threshold for Feature Selecti...
Estimate PCC of HCT Classifiers
Estimate PCC of HCT Classifiers via implementation of Monte Carlo simu...
Estimate PCC of HCT Classifiers via implementation of Monte Carlo simu...
Estimate PCC of HCT Classifiers constructed with correlated features u...
Sample Size Calculation for High Dimensional Classification Study
Determine the Ideal PCC
Determine the Sample Size Requirement
Determine the Feasibility Region
Determine the sample size requirement to achieve the target probability of correct classification (PCC) for studies employing high-dimensional features. The package implements functions to 1) determine the asymptotic feasibility of the classification problem; 2) compute the upper bounds of the PCC for any linear classifier; 3) estimate the PCC of three design methods given design assumptions; 4) determine the sample size requirement to achieve the target PCC for three design methods.