Density, distribution function, quantile function and random generation for the asymptotic null distribution of t* in the mixed case. That is, in the case that t* is generated a sample from an independent bivariate distribution where one coordinate is marginally discrete and the other marginally continuous.
pMixHoeffInd(x, probs, lower.tail = TRUE, error = 10^-6)dMixHoeffInd(x, probs, error = 10^-3)
rMixHoeffInd(n, probs, error = 10^-8)
qMixHoeffInd(p, probs, error = 10^-4)
dMixHoeffInd gives the density, pMixHoeffInd gives the distribution function, qMixHoeffInd gives the quantile function, and rMixHoeffInd generates random samples.
the value (or vector of values) at which to evaluate the function.
a vector of probabilities corresponding to the (ordered) support the marginally discrete random variable. That is, if the marginally discrete distribution has support \(u_1,...,u_n\) then the ith entry of probs should be the probability of seeing \(u_i\).
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.