This function computes the p-value of the khi2 goodness-of-fit test (only for univariate data).
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.
Returns
the p-value of the test.
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)