Density, distribution function, quantile function and random generation for the asymptotic null distribution of t* in the discrete case. That is, in the case that t* is generated from a sample of jointly discrete independent random variables X and Y.
pDisHoeffInd(x, probs1, probs2, lower.tail = TRUE, error = 10^-5)dDisHoeffInd(x, probs1, probs2, error = 10^-3)
rDisHoeffInd(n, probs1, probs2)
qDisHoeffInd(p, probs1, probs2, error = 10^-4)
dDisHoeffInd gives the density, pDisHoeffInd gives the distribution function, qDisHoeffInd gives the quantile function, and rDisHoeffInd generates random samples.
the value (or vector of values) at which to evaluate the function.
a vector of probabilities corresponding to the (ordered) support of X. That is if your first random variable has support \(u_1,...,u_n\) then the ith entry of probs should be \(P(X = u_i)\).
just as probs1 but for the second random variable Y.
a logical value, if TRUE (default), probabilities are \(P(X\leq x)\) otherwise \(P(X>x)\).
a tolerated error in the result. This should be considered as a guide rather than an exact upper bound to the amount of error.
the number of observations to return.
the probability (or vector of probabilities) for which to get the quantile.