khi2 {Rankcluster} | R Documentation |
Khi2 test
Description
This function computes the p-value of the khi2 goodness-of-fit test (only for univariate data).
Usage
khi2(data, proportion, mu, pi, nBoot = 1000)
Arguments
data |
a matrix in which each row is a rank of size m. |
proportion |
a vector (which sums to 1) containing the K mixture proportion. |
mu |
a matrix of size K*m, where m is the size of a rank, containing the modal rankings of the model (position parameters). |
pi |
a vector of size K, where K is the number of clusters, containing the probabilities of a good paired comparison of the model (dispersion parameters). |
nBoot |
number of bootstrap iterations used to estimate the p-value. |
Value
the p-value of the test.
Author(s)
Quentin Grimonprez
Examples
proportion <- c(0.4, 0.6)
pi <- c(0.8, 0.75)
mu <- matrix(c(1, 2, 3, 4, 4, 2, 1, 3), nrow = 2, byrow = TRUE)
# simulate a data set with declared parameters.
data <- rbind(
simulISR(proportion[1] * 100, pi[1], mu[1, ]),
simulISR(proportion[2] * 100, pi[2], mu[2, ])
)
pval <- khi2(data, proportion, mu, pi)
[Package Rankcluster version 0.98.0 Index]