| add_interaction_terms | Creates interaction terms for specified variables in a data frame Interaction terms are named as '<var1>_int_<var2>' (e.g., 'Z1_int_Z2' for the product of 'Z1' and 'Z2'). |
| add_poly_terms | Creates polynomial terms for specified variables in a data frame Polynomial terms are named as '<variable>_d_<degree>' (e.g., 'Z1_d_2' for the square of 'Z1'). |
| BinaryData | Generate Binary Data |
| BivMultinominal | Generate Bivariate Multinomial Categorical Data |
| BivNonLinearCategorization | Generate Bivariate Nonlinear Categorical Data |
| build_formula | Build an expanded formula with poly and interaction terms |
| CCI | Computational test for conditional independence based on ML and Monte Carlo Cross Validation |
| CCI.direction | Choose Direction for testing for the CCI test |
| CCI.pretuner | CCI tuner function for CCI test |
| CCI.test | Computational test for conditional independence based on ML and Monte Carlo Cross Validation |
| check_formula | Check the formula statement |
| clean_formula | Clean and Reformat Formula String |
| ComplexCategorization | Generate Complex Categorical Data |
| ExpLogData | Generate Categorical Data Based on Exponential and Logarithmic Functions |
| ExpLogThreshold | Generate Exponential and Logarithmic Data |
| ExponentialNoise | Generate Data with Exponential Noise |
| get_pvalues | P-value Calculation Based on Null Distribution and Test Statistic |
| get_tuned_params | Get the best parameters after tuning with CCI.tuner |
| GridPartition | Generate Grid Partitioned Data |
| HardCase | Generate Hard Case Data with Two Z Variables |
| InteractiondData | Generate Categorical Data Based on Interactions |
| NonLinearCategorization | Generate Nonlinear Categorical Data (Univariate) |
| NonLinearData | Generate Nonlinear Categorical Data (Bivariate) |
| NonLinNormal | Generate Nonlinear Normal Data |
| NonLinNormalZs | Generate High-dimensional Nonlinear Normal Data |
| NormalData | Generate Normal Data for Conditional Independence Testing |
| perm.test | Permutation Test for Conditional Independence |
| plot.CCI | Plot for CCI testing |
| PoissonNoise | Generate Data with Poisson Noise |
| PolyData | Generate Categorical Polynomial Data |
| PolyDecision | Generate Polynomial Decision Boundary Data |
| print.CCI | Print and summary methods for the CCI class |
| print.summary.CCI | Print and summary methods for the CCI class |
| QQplot | QQ-plot for multiple testing in CCI |
| QuadThresh | Generate Quadratic Threshold Data |
| reports | Print and summary methods for the CCI class |
| SinCosThreshold | Generate Sinusoidal and Cosine Data |
| SineGaussian | Generate Sine-Gaussian Data (Univariate) |
| SineGaussianBiv | Generate Sine-Gaussian Data (Bivariate) |
| SineGaussianNoise | Generate Sine-Gaussian Data (Bivariate) |
| summary.CCI | Print and summary methods for the CCI class |
| test.gen | Generate the Test Statistic or Null Distribution Using Permutation |
| TrigData | Generate Categorical Trigonometric Data |
| tuner | CCI tuner function for CCI test |
| UniformNoise | Generate Data with Uniform Noise |
| wrapper_ranger | Random Forest wrapper for CCI |
| wrapper_svm | SVM wrapper for CCI |
| wrapper_xgboost | Extreme Gradient Boosting wrapper for CCI |