Package: CCI 0.3.6.1

Christian Thorjussen

CCI: Computational Test for Conditional Independence

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>.

Authors:Christian Thorjussen [aut, cre], Kristian Hovde Liland [aut]

CCI_0.3.6.1.tar.gz
CCI_0.3.6.1.zip(r-4.7)CCI_0.3.6.1.zip(r-4.6)CCI_0.3.6.1.zip(r-4.5)
CCI_0.3.6.1.tgz(r-4.6-any)CCI_0.3.6.1.tgz(r-4.5-any)
CCI_0.3.6.1.tar.gz(r-4.7-any)CCI_0.3.6.1.tar.gz(r-4.6-any)
CCI_0.3.6.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
CCI/json (API)

# Install 'CCI' in R:

install.packages('CCI', repos = c('https://khliland.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/khliland/cci/issues

Datasets:

ExponentialNoise - Example dataset: ExponentialNoise
HardCase - Example dataset: HardCase
NonLinearCategorization - Example dataset: NonLinearCategorization
NonLinNormal - Example dataset: NonLinNormal
NonLinNormalZs_d0 - Example dataset: NonLinNormalZs_d0
NonLinNormalZs_d05 - Example dataset: NonLinNormalZs_d05
NormalData - Example dataset: NormalData
PoissonNoise - Example dataset: PoissonNoise
PolyData - Example dataset: PolyData
UniformNoise_large - Example dataset: UniformNoise_large

On CRAN:

5.18 score 2 stars 6 scripts 200 downloads 21 exports 83 dependencies

Last updated from:b3c319acc0. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	234
source / vignettes	OK	395
linux-release-x86_64	OK	232
macos-release-arm64	OK	118
macos-oldrel-arm64	OK	150
windows-devel	OK	144
windows-release	OK	149
windows-oldrel	OK	144
wasm-release	OK	126

Exports:add_interaction_terms add_poly_terms build_formula CCI.direction CCI.pretuner CCI.test check_formula clean_formula get_pvalues get_tuned_params is_categorical_Z_any make_strata_from_categorical_Z perm.test permute_within_strata QQplot test.gen unclean_formula wrapper_knn wrapper_ranger wrapper_svm wrapper_xgboost

Dependencies:caret class cli clock codetools cpp11 crayon data.table diagram digest dplyr e1071 farver foreach future future.apply generics ggplot2 globals glue gower gtable hardhat hms igraph ipred isoband iterators jsonlite KernSmooth kknn labeling lattice lava lifecycle listenv lubridate magrittr MASS Matrix ModelMetrics nlme nnet numDeriv parallelly pillar pkgconfig plyr prettyunits pROC prodlim progress progressr proxy purrr R6 ranger RColorBrewer Rcpp RcppEigen recipes reshape2 rlang rpart S7 scales shape sparsevctrs SQUAREM stringi stringr survival tibble tidyr tidyselect timechange timeDate tzdb utf8 vctrs viridisLite withr xgboost

Conditional Independence Testing with CCI

Rendered fromTesting-CI-with-CCI.Rmdusingknitr::rmarkdown

Last update: 2026-01-16
Started: 2026-01-16

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
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_interaction_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').	add_poly_terms
Build an expanded formula with poly and interaction terms	build_formula
Choose Direction for testing for the CCI test	CCI.direction
CCI tuner function for CCI test	CCI.pretuner tuner
Computational test for conditional independence based on ML and Monte Carlo Cross Validation	CCI CCI.test
Check the formula statement	check_formula
Clean and Reformat Formula String	clean_formula
Example dataset: ExponentialNoise	ExponentialNoise
P-value Calculation Based on Null Distribution and Test Statistic	get_pvalues
Get the best parameters after tuning with CCI.tuner	get_tuned_params
Example dataset: HardCase	HardCase
Check whether Z contains at least one categorical variable	is_categorical_Z_any
Create strata from the categorical subset of Z	make_strata_from_categorical_Z
Example dataset: NonLinearCategorization	NonLinearCategorization
Example dataset: NonLinNormal	NonLinNormal
Example dataset: NonLinNormalZs_d0	NonLinNormalZs_d0
Example dataset: NonLinNormalZs_d05	NonLinNormalZs_d05
Example dataset: NormalData	NormalData
Permutation Test for Conditional Independence	perm.test
Stratified permutation of x within strata	permute_within_strata
Plot for CCI testing	plot.CCI
Example dataset: PoissonNoise	PoissonNoise
Example dataset: PolyData	PolyData
Print and summary methods for the CCI class	print.CCI print.summary.CCI reports summary.CCI
QQ-plot for multiple testing in CCI	QQplot
Generate the Test Statistic or Null Distribution Using Permutation	test.gen
Convert CI-style formula Y ~ X \| Z into regression-style Y ~ X + Z	unclean_formula
Example dataset: UniformNoise_large	UniformNoise_large
k-Nearest Neighbors (KNN) wrapper for CCI (kknn-based)	wrapper_knn
Random Forest wrapper for CCI	wrapper_ranger
SVM wrapper for CCI	wrapper_svm
Extreme Gradient Boosting wrapper for CCI	wrapper_xgboost