| allElementsAreNonNegative(std::span< const IntType > sample) | randlib::UnivariateDistribution< IntType > | protectedstatic |
| allElementsAreNotGreaterThan(IntType value, std::span< const IntType > sample) | randlib::UnivariateDistribution< IntType > | protectedstatic |
| allElementsAreNotSmallerThan(IntType value, std::span< const IntType > sample) | randlib::UnivariateDistribution< IntType > | protectedstatic |
| allElementsArePositive(std::span< const IntType > sample) | randlib::UnivariateDistribution< IntType > | protectedstatic |
| BernoulliRand(double probability=0.5) | randlib::BernoulliRand | inlineexplicit |
| BinomialDistribution(int number, double probability) | randlib::BinomialDistribution< int > | protected |
| CarrierMeasure(int x) const override | randlib::BinomialDistribution< int > | |
| randlib::ExponentialFamily::CarrierMeasure(T x) const =0 | randlib::ExponentialFamily< T, P > | pure virtual |
| CF(double t) const | randlib::UnivariateDistribution< IntType > | |
| CharacteristicFunction(std::span< const double > t, std::span< std::complex< double > > y) const | randlib::UnivariateDistribution< IntType > | |
| CrossEntropyAdjusted(P parameters) const | randlib::ExponentialFamily< T, P > | virtual |
| CumulativeDistributionFunction(std::span< const T > x, std::span< double > y) const | randlib::ProbabilityDistribution< T > | |
| DiscreteDistribution() | randlib::DiscreteDistribution< IntType > | inlineprotected |
| engine() const | randlib::ProbabilityDistribution< T > | inlineprotected |
| Entropy() | randlib::BernoulliRand | inline |
| EntropyAdjusted() const override | randlib::BinomialDistribution< int > | virtual |
| ExcessKurtosis() const override | randlib::BinomialDistribution< int > | virtual |
| ExpectedValue(const std::function< double(IntType)> &funPtr, IntType minPoint, IntType maxPoint) const override | randlib::DiscreteDistribution< IntType > | protectedvirtual |
| ExponentialFamily() | randlib::ExponentialFamily< T, P > | inline |
| F(const int &k) const override | randlib::BernoulliRand | inline |
| BinomialDistribution< int >::F(const int &k) const override | randlib::BinomialDistribution< int > | |
| randlib::DiscreteDistribution::F(const T &x) const =0 | randlib::ProbabilityDistribution< T > | pure virtual |
| fitError(FitErrorCode code, const std::string &explanation) const | randlib::ProbabilityDistribution< T > | protected |
| FitProbability(std::span< const int > sample) | randlib::BinomialDistribution< int > | |
| FitProbabilityBayes(std::span< const int > sample, const BetaDistribution<> &priorDistribution, bool MAP=false) | randlib::BinomialDistribution< int > | |
| FitProbabilityMinimax(std::span< const int > sample) | randlib::BinomialDistribution< int > | |
| FourthMoment() const | randlib::UnivariateDistribution< IntType > | virtual |
| GetLog1mProbability() const noexcept | randlib::BinomialDistribution< int > | inline |
| GetLogFactorialN() const noexcept | randlib::BinomialDistribution< int > | inline |
| GetLogProbability() const noexcept | randlib::BinomialDistribution< int > | inline |
| GetNumber() const noexcept | randlib::BinomialDistribution< int > | inline |
| GetProbability() const noexcept | randlib::BinomialDistribution< int > | inline |
| GetSampleLogMean(std::span< const IntType > sample) | randlib::UnivariateDistribution< IntType > | static |
| GetSampleLogMeanAndVariance(std::span< const IntType > sample) | randlib::UnivariateDistribution< IntType > | static |
| GetSampleLogVariance(std::span< const IntType > sample, double logMean) | randlib::UnivariateDistribution< IntType > | static |
| GetSampleMean(std::span< const IntType > sample) | randlib::UnivariateDistribution< IntType > | static |
| GetSampleMeanAndVariance(std::span< const IntType > sample) | randlib::UnivariateDistribution< IntType > | static |
| GetSampleStatistics(std::span< const IntType > sample) | randlib::UnivariateDistribution< IntType > | static |
| GetSampleSum(std::span< const IntType > sample) | randlib::UnivariateDistribution< IntType > | static |
| GetSampleVariance(std::span< const IntType > sample, double mean) | randlib::UnivariateDistribution< IntType > | static |
| Hazard(const IntType &x) const override | randlib::DiscreteDistribution< IntType > | virtual |
| HazardFunction(std::span< const IntType > x, std::span< double > y) const | randlib::UnivariateDistribution< IntType > | |
| isLeftBounded() const | randlib::UnivariateDistribution< IntType > | |
| isRightBounded() const | randlib::UnivariateDistribution< IntType > | |
| KullbackLeiblerDivergence(P parameters) const | randlib::ExponentialFamily< T, P > | |
| Kurtosis() const | randlib::UnivariateDistribution< IntType > | virtual |
| LikelihoodFunction(std::span< const IntType > sample) const override | randlib::DiscreteDistribution< IntType > | virtual |
| log1mProb | randlib::BinomialDistribution< int > | protected |
| LogLikelihoodFunction(std::span< const IntType > sample) const override | randlib::DiscreteDistribution< IntType > | virtual |
| LogNormalizer(double theta) const override | randlib::BinomialDistribution< int > | |
| randlib::ExponentialFamily::LogNormalizer(P theta) const =0 | randlib::ExponentialFamily< T, P > | pure virtual |
| LogNormalizerGradient(double theta) const override | randlib::BinomialDistribution< int > | |
| randlib::ExponentialFamily::LogNormalizerGradient(P theta) const =0 | randlib::ExponentialFamily< T, P > | pure virtual |
| logP(const int &k) const override | randlib::BernoulliRand | inline |
| BinomialDistribution< int >::logP(const int &k) const override | randlib::BinomialDistribution< int > | virtual |
| logProb | randlib::BinomialDistribution< int > | protected |
| LogProbabilityMassFunction(std::span< const IntType > x, std::span< double > y) const | randlib::DiscreteDistribution< IntType > | |
| LogProbabilityMeasure(T x) const | randlib::ExponentialFamily< T, P > | |
| LOWER_LIMIT_VIOLATION | randlib::ProbabilityDistribution< T > | protectedstatic |
| MAX_ITER_REJECTION | randlib::ProbabilityDistribution< T > | protectedstatic |
| MaxValue() const override | randlib::BinomialDistribution< int > | inlinevirtual |
| Mean() const override | randlib::BinomialDistribution< int > | virtual |
| Median() const override | randlib::BinomialDistribution< int > | virtual |
| MinValue() const override | randlib::BinomialDistribution< int > | inlinevirtual |
| Mode() const override | randlib::BinomialDistribution< int > | virtual |
| Name() const override | randlib::BernoulliRand | inlinevirtual |
| NaturalParameters() const override | randlib::BinomialDistribution< int > | virtual |
| NON_NEGATIVITY_VIOLATION | randlib::ProbabilityDistribution< T > | protectedstatic |
| operator()(G &g) const | randlib::BernoulliRand | |
| p | randlib::BinomialDistribution< int > | protected |
| P(const int &k) const override | randlib::BernoulliRand | inline |
| BinomialDistribution< int >::P(const int &k) const override | randlib::BinomialDistribution< int > | virtual |
| PearsonChiSquaredTest(std::span< const IntType > orderStatistic, double alpha, int lowerBoundary, int upperBoundary, size_t numberOfEstimatedParameters=0) const | randlib::DiscreteDistribution< IntType > | |
| PearsonChiSquaredTest(std::span< const IntType > orderStatistic, double alpha, size_t numberOfEstimatedParameters=0) const | randlib::DiscreteDistribution< IntType > | |
| POSITIVITY_VIOLATION | randlib::ProbabilityDistribution< T > | protectedstatic |
| ProbabilityDistribution()=default | randlib::ProbabilityDistribution< T > | protected |
| ProbabilityMassFunction(std::span< const IntType > x, std::span< double > y) const | randlib::DiscreteDistribution< IntType > | |
| ProbabilityMeasure(T x) const | randlib::ExponentialFamily< T, P > | |
| q | randlib::BinomialDistribution< int > | protected |
| Quantile(double p) const | randlib::UnivariateDistribution< IntType > | |
| Quantile1m(double p) const | randlib::UnivariateDistribution< IntType > | |
| QuantileFunction(std::span< const double > p, std::span< IntType > y) const | randlib::UnivariateDistribution< IntType > | |
| QuantileFunction1m(std::span< const double > p, std::span< IntType > y) const | randlib::UnivariateDistribution< IntType > | |
| quantileImpl(double p, IntType initValue) const override | randlib::DiscreteDistribution< IntType > | protectedvirtual |
| quantileImpl(double p) const override | randlib::DiscreteDistribution< IntType > | protectedvirtual |
| quantileImpl1m(double p, IntType initValue) const override | randlib::DiscreteDistribution< IntType > | protectedvirtual |
| quantileImpl1m(double p) const override | randlib::DiscreteDistribution< IntType > | protectedvirtual |
| Reseed(std::uint64_t seed) | randlib::ProbabilityDistribution< T > | inline |
| S(const int &k) const override | randlib::BernoulliRand | inline |
| BinomialDistribution< int >::S(const int &k) const override | randlib::BinomialDistribution< int > | |
| randlib::DiscreteDistribution::S(const T &x) const | randlib::ProbabilityDistribution< T > | virtual |
| Sample(std::span< T > outputData) const | randlib::ProbabilityDistribution< T > | inline |
| Sample(G &g, std::span< T > outputData) const | randlib::ProbabilityDistribution< T > | inline |
| randlib::DiscreteDistribution::sample(detail::EngineRef g, std::span< T > outputData) const | randlib::ProbabilityDistribution< T > | inlineprotectedvirtual |
| SecondMoment() const | randlib::UnivariateDistribution< IntType > | virtual |
| SetParameters(int number, double probability) | randlib::BinomialDistribution< int > | protected |
| SetProbability(double probability) | randlib::BernoulliRand | inline |
| Skewness() const override | randlib::BinomialDistribution< int > | virtual |
| SourceParameters() const override | randlib::BinomialDistribution< int > | virtual |
| SourceToNatural(double sourceParameters) const override | randlib::BinomialDistribution< int > | |
| randlib::ExponentialFamily::SourceToNatural(P sourceParameters) const =0 | randlib::ExponentialFamily< T, P > | pure virtual |
| StandardVariate(G &g) | randlib::BernoulliRand | static |
| SufficientStatistic(int x) const override | randlib::BinomialDistribution< int > | |
| randlib::ExponentialFamily::SufficientStatistic(T x) const =0 | randlib::ExponentialFamily< T, P > | pure virtual |
| SupportType() const override | randlib::BinomialDistribution< int > | inlinevirtual |
| SurvivalFunction(std::span< const T > x, std::span< double > y) const | randlib::ProbabilityDistribution< T > | |
| ThirdMoment() const | randlib::UnivariateDistribution< IntType > | virtual |
| toStringWithPrecision(const double a_value, const int n=6) const | randlib::ProbabilityDistribution< T > | protected |
| UnivariateDistribution() | randlib::UnivariateDistribution< IntType > | protected |
| UPPER_LIMIT_VIOLATION | randlib::ProbabilityDistribution< T > | protectedstatic |
| value_type typedef | randlib::ProbabilityDistribution< T > | |
| Variance() const override | randlib::BinomialDistribution< int > | virtual |
| Variate(double probability, G &g) | randlib::BernoulliRand | static |
| BinomialDistribution< int >::Variate(int number, double probability, G &g) | randlib::BinomialDistribution< int > | static |
| randlib::DiscreteDistribution::Variate() const | randlib::ProbabilityDistribution< T > | inline |
| ~DiscreteDistribution() | randlib::DiscreteDistribution< IntType > | inlinevirtual |
| ~ExponentialFamily() | randlib::ExponentialFamily< T, P > | inlinevirtual |
| ~ProbabilityDistribution()=default | randlib::ProbabilityDistribution< T > | virtual |
| ~UnivariateDistribution() | randlib::UnivariateDistribution< IntType > | inlinevirtual |
1.9.8