Chi-square and G-square tests of (unconditional) indepdence
Chi-square and G-square tests of (unconditional) indepdence.
cat.tests(x, y, logged = FALSE)
x |
A numerical vector or a factor variable with data. The data must be consecutive numbers. |
y |
A numerical vector or a factor variable with data. The data must be consecutive numbers. |
logged |
Should the p-values be returned (FALSE) or their logarithm (TRUE)? |
The function calculates the test statistic of the X^2 and the G^2 tests of unconditional
independence between x and y. x and y need not be numerical vectors like in g2Test. This
function is more close to the spirit of MASS' loglm function which calculates both statistics
using Poisson log-linear models (Tsagris, 2017).
A matrix with two rows. In each row the X2 or G2 test statistic, its p-value and the degrees of freedom are returned.
Michail Tsagris.
R implementation and documentation: Michail Tsagris mtsagris@uoc.gr.
Tsagris M. (2021). A new scalable Bayesian network learning algorithm with applications to economics. Computational Economics (Accepted for publication).
Tsagris M. (2017). Conditional independence test for categorical data using Poisson log-linear model. Journal of Data Science, 15(2): 347-356.
x <- rbinom(100, 3, 0.5) y <- rbinom(100, 2, 0.5) cat.tests(x, y)
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