Computational Test for Conditional Independence
Creates interaction terms for specified variables in a data frame Inte...
Creates polynomial terms for specified variables in a data frame Polyn...
Build an expanded formula with poly and interaction terms
Choose Direction for testing for the CCI test
CCI tuner function for CCI test
Computational test for conditional independence based on ML and Monte ...
Check the formula statement
Clean and Reformat Formula String
P-value Calculation Based on Null Distribution and Test Statistic
Get the best parameters after tuning with CCI.tuner
Check whether Z contains at least one categorical variable
Create strata from the categorical subset of Z
Permutation Test for Conditional Independence
Stratified permutation of x within strata
Plot for CCI testing
QQ-plot for multiple testing in CCI
Print and summary methods for the CCI class
Generate the Test Statistic or Null Distribution Using Permutation
Convert CI-style formula Y ~ X | Z into regression-style Y ~ X + Z
k-Nearest Neighbors (KNN) wrapper for CCI (kknn-based)
Random Forest wrapper for CCI
SVM wrapper for CCI
Extreme Gradient Boosting wrapper for CCI
Tool for performing computational testing for conditional independence between variables in a dataset. 'CCI' implements permutation in combination with Monte Carlo Cross-Validation in generating null distributions and test statistics. For more details see Computational Test for Conditional Independence (2024) <doi:10.3390/a17080323>.