Chi-square and G-square tests of (unconditional) indepdence {Rfast}

Chi-square and G-square tests of (unconditional) indepdence

Description

Chi-square and G-square tests of (unconditional) indepdence.

Usage

gchi2Test(x, y, logged = FALSE)

Arguments

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)?

Details

The function calculates the test statistic of the \chi^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).

Value

A matrix with two rows. In each row the X2 or G2 test statistic, its p-value and the degrees of freedom are returned.

Author(s)

Manos Papadakis and Michail Tsagris

R implementation and documentation: Manos Papadakis <[e-mail]> and Michail Tsagris <[e-mail]>.

References

Tsagris M. (2017). Conditional independence test for categorical data using Poisson log-linear model. Journal of Data Science, 15(2):347-356.

See Also

g2Test_univariate, g2Test_univariate_perm, g2Test

Examples

nvalues <- 3
nvars <- 2
nsamples <- 5000
data <- matrix( sample( 0:(nvalues - 1), nvars * nsamples, replace = TRUE ), nsamples, nvars )

res<-gchi2Test(data[, 1], data[, 2])
res<-g2Test_univariate( data, rep(3, 2) )  ## G^2 test
res<-chisq.test(data[, 1], data[, 2])  ## X^2 test from R
  
data<-NULL