Implements fast Monte Carlo simulations for 
    goodness-of-fit (GOF) tests for discrete distributions. This 
    includes tests based on the Chi-squared statistic, the 
    log-likelihood-ratio (G^2) statistic, the Freeman-Tukey 
    (Hellinger-distance) statistic, the Kolmogorov-Smirnov 
    statistic, the Cramer-von Mises statistic as described in 
    Choulakian, Lockhart and Stephens (1994) <doi:10.2307/3315828>, 
    and the root-mean-square statistic, see Perkins, 
    Tygert, and Ward (2011) <doi:10.1016/j.amc.2011.03.124>.

Probability mass function, distribution function, quantile function, random generation and parameter estimation for the discrete inverse Weibull distribution.

Probability mass function, distribution function, quantile function, random generation and estimation for the skew discrete Laplace distributions.

We consider a multiple testing procedure used in many modern applications which is the q-value method proposed by Storey and Tibshirani (2003), <doi:10.1073/pnas.1530509100>. The q-value method is based on the false discovery rate (FDR), hence versions of the q-value method can be defined depending on which estimator of the proportion of true null hypotheses, p0, is plugged in the FDR estimator. We implement the q-value method based on two classical pi0 estimators, and furthermore, we propose and implement three versions of the q-value method for homogeneous discrete uniform P-values based on pi0 estimators which take into account the discrete distribution of the P-values.

Provides vectorised functions for computing p-values of various
    common discrete statistical tests as described e.g. in Agresti (2002)
    <doi:10.1002/0471249688>. Exact and approximate computation methods are
    provided. For exact p-values, several procedures of determining two-sided
    p-values are included, which are outlined in more detail in Hirji (2006)
    <doi:10.1201/9781420036190>.

Probability mass function, distribution function, quantile function, random generation and parameter estimation for the type I and III discrete Weibull distributions.