Improved q-Values for Discrete Uniform and Homogeneous Tests
c(
person("Marta", "Cousido Rocha", email = "martacousido@uvigo.es", role = c("aut", "cre")),
person("José Carlos", "Soage González", email = "jsoage@uvigo.es", role = "ctr"),
person("Jacobo", "de Uña Álvarez", email = "jacobo@uvigo.es", role = c("aut", "ths")),
person("Sebastian", "Döhler", role = "aut"))
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, pi_0, is plugged in the FDR estimator. We implement the q-value method based on two classical pi_0 estimators, and furthermore, we propose and implement three versions of the q-value method for homogeneous discrete uniform P-values based on pi_0 estimators which take into account the discrete distribution of the P-values.
Marta Cousido Rocha [aut, cre],
José Carlos Soage González [ctr],
Jacobo de Uña Álvarez [aut, ths],
Sebastian Döhler [aut]

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.

Discrete Weibull Distributions (Type 1 and 3)
Probability mass function, distribution function, quantile function, random generation and parameter estimation for the type I and III discrete Weibull distributions.