| Type: | Package | 
| Title: | Uniform Exact Functional Tests for Contingency Tables | 
| Version: | 1.0.1 | 
| Date: | 2025-02-20 | 
| Author: | Yiyi Li | 
| Maintainer: | Yiyi Li <gtarex@nmsu.edu> | 
| Description: | Testing whether two discrete variables have a functional relationship under null distributions where the two variables are statistically independent with fixed marginal counts. The fast enumeration algorithm was based on (Nguyen et al. 2020) <doi:10.24963/ijcai.2020/372>. | 
| License: | LGPL (≥ 3) | 
| Encoding: | UTF-8 | 
| Imports: | Rcpp (≥ 1.0.5) | 
| LinkingTo: | Rcpp | 
| Depends: | R (≥ 3.5.0), stats | 
| Suggests: | knitr, rmarkdown, testthat (≥ 3.0.0) | 
| VignetteBuilder: | knitr | 
| Config/testthat/edition: | 3 | 
| RoxygenNote: | 7.3.2 | 
| NeedsCompilation: | yes | 
| Packaged: | 2025-02-21 06:36:22 UTC; gtarex | 
| Repository: | CRAN | 
| Date/Publication: | 2025-02-21 07:00:02 UTC | 
Uniform Exact Functional Test on Two Discrete Random Variables
Description
Perform the uniform exact functional test on a contingency table to determine if the column variable is a function of the row variable.
Usage
UEFT(input, correct, log.p)
Arguments
| input | A matrix of nonnegative integers representing a contingency table. Column is the casual and row is the effect. | 
| correct | Logical; if implement the continuity correction. The description is at details. The default is TRUE. | 
| log.p | Logical; if TRUE, the p-value is given as log(p). The default is FALSE. The default is FALSE. | 
Details
The uniform idea was implementated using uniform marginal distribution of a square table as null hypothesis.
Value
The exact p-value of the test.
Note
The functions provide a direct entry into the C++ implementations of the exact functional test.
Author(s)
Yiyi Li, Joe Song
Examples
 # Initial a table
 x = matrix(c(0,5,10,0,0,5), ncol=3)
 # With continuity correction
 UEFT(x)
 # Without continuity correction
 UEFT(x, FALSE)