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...
Generate Binary Data
Generate Bivariate Multinomial Categorical Data
Generate Bivariate Nonlinear Categorical Data
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
Generate Complex Categorical Data
Generate Categorical Data Based on Exponential and Logarithmic Functio...
Generate Exponential and Logarithmic Data
Generate Data with Exponential Noise
P-value Calculation Based on Null Distribution and Test Statistic
Get the best parameters after tuning with CCI.tuner
Generate Grid Partitioned Data
Generate Hard Case Data with Two Z Variables
Generate Categorical Data Based on Interactions
Generate Nonlinear Categorical Data (Univariate)
Generate Nonlinear Categorical Data (Bivariate)
Generate Nonlinear Normal Data
Generate High-dimensional Nonlinear Normal Data
Generate Normal Data for Conditional Independence Testing
Permutation Test for Conditional Independence
Plot for CCI testing
Generate Data with Poisson Noise
Generate Categorical Polynomial Data
Generate Polynomial Decision Boundary Data
QQ-plot for multiple testing in CCI
Generate Quadratic Threshold Data
Print and summary methods for the CCI class
Generate Sinusoidal and Cosine Data
Generate Sine-Gaussian Data (Univariate)
Generate Sine-Gaussian Data (Bivariate)
Generate Sine-Gaussian Data (Bivariate)
Generate the Test Statistic or Null Distribution Using Permutation
Generate Categorical Trigonometric Data
Generate Data with Uniform Noise
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>.