The OpenD Programming Language

mir.stat.distribution.cdf

This package publicly imports mir.stat.distribution.*CDF modules.

FunctionsDescription
Univariate Discrete Distributions
bernoulliCDFBernoulli CDF
binomialCDFBinomial CDF
geometricCDFGeometric CDF
hypergeometricCDFHypergeometric CDF
negativeBinomialCDFNegative Binomial CDF
poissonCDFPoisson CDF
uniformDiscreteCDFDiscrete Uniform CDF
Univariate Continuous Distributions
betaCDFBeta CDF
betaProportionCDFBeta Proportion CDF
cauchyCDFCauchy CDF
chi2CDFChi-squared CDF
exponentialCDFExponential CDF
fCDFF CDF
gammaCDFGamma CDF
generalizedParetoCDFGeneralized Pareto CDF
gevCDFGeneralized Extreme Value (GEV) CDF
laplaceCDFLaplace CDF
logNormalCDFLog-normal CDF
logisticCDFLogistic CDF
normalCDFNormal CDF
paretoCDFPareto CDF
rayleighCDFRayleigh CDF
studentsTCDFStudent's t CDF
uniformCDFContinuous Uniform CDF
weibullCDFWeibull CDF
Multivariate Distributions
categoricalCDFCategorical CDF

Members

Functions

bernoulliCDF (from mir.stat.distribution.bernoulli)
T bernoulliCDF(bool x, T p) via public import mir.stat.distribution.bernoulli : bernoulliCDF;
betaCDF (from mir.stat.distribution.beta)
T betaCDF(T x, T alpha, T beta) via public import mir.stat.distribution.beta : betaCDF;
betaProportionCDF (from mir.stat.distribution.beta_proportion)
T betaProportionCDF(T x, T mu, T kappa) via public import mir.stat.distribution.beta_proportion : betaProportionCDF;
categoricalCDF (from mir.stat.distribution.categorical)
T categoricalCDF(size_t x, T[] p) via public import mir.stat.distribution.categorical : categoricalCDF;
cauchyCDF (from mir.stat.distribution.cauchy)
T cauchyCDF(T x, T location, T scale) via public import mir.stat.distribution.cauchy : cauchyCDF;
chi2CDF (from mir.stat.distribution.chi2)
T chi2CDF(T x, uint k) via public import mir.stat.distribution.chi2 : chi2CDF;
exponentialCDF (from mir.stat.distribution.exponential)
T exponentialCDF(T x, T lambda) via public import mir.stat.distribution.exponential : exponentialCDF;
fCDF (from mir.stat.distribution.f)
T fCDF(T x, T df1, T df2) via public import mir.stat.distribution.f : fCDF;
gammaCDF (from mir.stat.distribution.gamma)
T gammaCDF(T x, T shape, T scale) via public import mir.stat.distribution.gamma : gammaCDF;
generalizedParetoCDF (from mir.stat.distribution.generalized_pareto)
T generalizedParetoCDF(T x, T mu, T sigma, T xi) via public import mir.stat.distribution.generalized_pareto : generalizedParetoCDF;
geometricCDF (from mir.stat.distribution.geometric)
T geometricCDF(T x, T p) via public import mir.stat.distribution.geometric : geometricCDF;
gevCDF (from mir.stat.distribution.gev)
T gevCDF(T x, T mu, T sigma, T xi) via public import mir.stat.distribution.gev : gevCDF;
laplaceCDF (from mir.stat.distribution.laplace)
T laplaceCDF(T x, T location, T scale) via public import mir.stat.distribution.laplace : laplaceCDF;
logNormalCDF (from mir.stat.distribution.log_normal)
T logNormalCDF(T x, T mean, T stdDev) via public import mir.stat.distribution.log_normal : logNormalCDF;
logisticCDF (from mir.stat.distribution.logistic)
T logisticCDF(T x, T location, T scale) via public import mir.stat.distribution.logistic : logisticCDF;
negativeBinomialCDF (from mir.stat.distribution.negative_binomial)
T negativeBinomialCDF(size_t k, size_t r, T p) via public import mir.stat.distribution.negative_binomial : negativeBinomialCDF;
paretoCDF (from mir.stat.distribution.pareto)
T paretoCDF(T x, T xMin, T alpha) via public import mir.stat.distribution.pareto : paretoCDF;
rayleighCDF (from mir.stat.distribution.rayleigh)
T rayleighCDF(T x, T scale) via public import mir.stat.distribution.rayleigh : rayleighCDF;
studentsTCDF (from mir.stat.distribution.students_t)
T studentsTCDF(T x, T nu, T mean, T stdDev) via public import mir.stat.distribution.students_t : studentsTCDF;
uniformCDF (from mir.stat.distribution.uniform)
T uniformCDF(T x, T lower, T upper) via public import mir.stat.distribution.uniform : uniformCDF;
uniformDiscreteCDF (from mir.stat.distribution.uniform_discrete)
double uniformDiscreteCDF(size_t x, size_t lower, size_t upper) via public import mir.stat.distribution.uniform_discrete : uniformDiscreteCDF;
weibullCDF (from mir.stat.distribution.weibull)
T weibullCDF(T x, T shape, T scale) via public import mir.stat.distribution.weibull : weibullCDF;

Imports

normalCDF (from mir.stat.distribution.normal)
public import mir.stat.distribution.normal : normalCDF;

Templates

binomialCDF (from mir.stat.distribution.binomial)
template binomialCDF(string binomialAlgo, string poissonAlgo = "gamma") via public import mir.stat.distribution.binomial : binomialCDF;
hypergeometricCDF (from mir.stat.distribution.hypergeometric)
template hypergeometricCDF(string hypergeometricAlgo) via public import mir.stat.distribution.hypergeometric : hypergeometricCDF;
poissonCDF (from mir.stat.distribution.poisson)
template poissonCDF(string poissonAlgo) via public import mir.stat.distribution.poisson : poissonCDF;

Meta

Authors

John Michael Hall, Ilya Yaroshenko