Report a bug
If you spot a problem with this page, click here to create a GitHub issue.
Improve this page
Quickly fork, edit online, and submit a pull request for this page. Requires a signed-in GitHub account. This works well for small changes. If you'd like to make larger changes you may want to consider using a local clone.


This package publicly imports mir.stat.distribution.*InvCDF modules.
    Univariate Discrete Distributions
bernoulliInvCDF  Bernoulli Inverse CDF
binomialInvCDF  Binomial Inverse CDF
geometricInvCDF  Geometric Inverse CDF
hypergeometricInvCDF  Hypergeometric Inverse CDF
negativeBinomialInvCDF  Negative Binomial Inverse CDF
poissonInvCDF  Poisson Inverse CDF
uniformDiscreteInvCDF  Discrete Uniform Inverse CDF
    Univariate Continuous Distributions
betaInvCDF  Beta Inverse CDF
betaProportionInvCDF  Beta Proportion Inverse CDF
cauchyInvCDF  Cauchy Inverse CDF
chi2InvCDF  Chi-squared Inverse CDF
exponentialInvCDF  Exponential Inverse CDF
fInvCDF  F Inverse CDF
gammaInvCDF  Gamma Inverse CDF
generalizedParetoInvCDF  Generalized Pareto Inverse CDF
gevInvCDF  Generalized Extreme Value (GEV) Inverse CDF
laplaceInvCDF  Laplace Inverse CDF
logNormalInvCDF  Log-normal Inverse CDF
logisticInvCDF  Logistic Inverse CDF
normalInvCDF  Normal Inverse CDF
paretoInvCDF  Pareto Inverse CDF
rayleighInvCDF  Rayleigh Inverse CDF
studentsTInvCDF  Student's t Inverse CDF
uniformInvCDF  Continuous Uniform Inverse CDF
weibullInvCDF  Weibull Inverse CDF
    Multivariate Distributions
categoricalInvCDF  Categorical Inverse CDF
John Michael Hall, Ilya Yaroshenko
public import mir.stat.distribution.bernoulli : bernoulliInvCDF;
public import mir.stat.distribution.beta : betaInvCDF;
public import mir.stat.distribution.beta_proportion : betaProportionInvCDF;
public import mir.stat.distribution.binomial : binomialInvCDF;
public import mir.stat.distribution.categorical : categoricalInvCDF;
public import mir.stat.distribution.cauchy : cauchyInvCDF;
public import mir.stat.distribution.chi2 : chi2InvCDF;
public import mir.stat.distribution.cornish_fisher : cornishFisherInvCDF;
public import mir.stat.distribution.exponential : exponentialInvCDF;
public import mir.stat.distribution.f : fInvCDF;
public import mir.stat.distribution.gamma : gammaInvCDF;
public import mir.stat.distribution.generalized_pareto : generalizedParetoInvCDF;
public import mir.stat.distribution.geometric : geometricInvCDF;
public import mir.stat.distribution.gev : gevInvCDF;
public import mir.stat.distribution.hypergeometric : hypergeometricInvCDF;
public import mir.stat.distribution.laplace : laplaceInvCDF;
public import mir.stat.distribution.log_normal : logNormalInvCDF;
public import mir.stat.distribution.logistic : logisticInvCDF;
public import mir.stat.distribution.negative_binomial : negativeBinomialInvCDF;
public import mir.stat.distribution.normal : normalInvCDF;
public import mir.stat.distribution.pareto : paretoInvCDF;
public import mir.stat.distribution.poisson : poissonInvCDF;
public import mir.stat.distribution.rayleigh : rayleighInvCDF;
public import mir.stat.distribution.students_t : studentsTInvCDF;
public import mir.stat.distribution.uniform : uniformInvCDF;
public import mir.stat.distribution.uniform_discrete : uniformDiscreteInvCDF;
public import mir.stat.distribution.weibull : weibullInvCDF;