RandLib 2.0.0
Probability distributions, fitting, and heavy-tail tools for C++20
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randlib::PoissonRand< IntType > Member List

This is the complete list of members for randlib::PoissonRand< IntType >, including all inherited members.

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
CarrierMeasure(IntType x) const overriderandlib::PoissonRand< IntType >virtual
CF(double t) constrandlib::UnivariateDistribution< IntType >
CharacteristicFunction(std::span< const double > t, std::span< std::complex< double > > y) constrandlib::UnivariateDistribution< IntType >
CrossEntropyAdjusted(double parameters) const overriderandlib::PoissonRand< IntType >
ExponentialFamily< IntType, double >::CrossEntropyAdjusted(double parameters) constrandlib::ExponentialFamily< IntType, double >virtual
CumulativeDistributionFunction(std::span< const T > x, std::span< double > y) constrandlib::ProbabilityDistribution< T >
DiscreteDistribution()randlib::DiscreteDistribution< IntType >inlineprotected
engine() constrandlib::ProbabilityDistribution< T >inlineprotected
EntropyAdjusted() const overriderandlib::PoissonRand< IntType >virtual
ExcessKurtosis() const overriderandlib::PoissonRand< IntType >virtual
ExpectedValue(const std::function< double(IntType)> &funPtr, IntType minPoint, IntType maxPoint) const overriderandlib::DiscreteDistribution< IntType >protectedvirtual
ExponentialFamily()randlib::ExponentialFamily< IntType, double >inline
F(const IntType &k) const overriderandlib::PoissonRand< IntType >
randlib::DiscreteDistribution::F(const T &x) const =0randlib::ProbabilityDistribution< T >pure virtual
Fit(std::span< const IntType > sample)randlib::PoissonRand< IntType >
Fit(std::span< const IntType > sample, DoublePair &confidenceInterval, double significanceLevel)randlib::PoissonRand< IntType >
FitBayes(std::span< const IntType > sample, const GammaDistribution<> &priorDistribution, bool MAP=false)randlib::PoissonRand< IntType >
fitError(FitErrorCode code, const std::string &explanation) constrandlib::ProbabilityDistribution< T >protected
FourthMoment() constrandlib::UnivariateDistribution< IntType >virtual
GetRate() const noexceptrandlib::PoissonRand< IntType >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 overriderandlib::DiscreteDistribution< IntType >virtual
HazardFunction(std::span< const IntType > x, std::span< double > y) constrandlib::UnivariateDistribution< IntType >
isLeftBounded() constrandlib::UnivariateDistribution< IntType >
isRightBounded() constrandlib::UnivariateDistribution< IntType >
KullbackLeiblerDivergence(double parameters) constrandlib::ExponentialFamily< IntType, double >
Kurtosis() constrandlib::UnivariateDistribution< IntType >virtual
LikelihoodFunction(std::span< const IntType > sample) const overriderandlib::DiscreteDistribution< IntType >virtual
LogLikelihoodFunction(std::span< const IntType > sample) const overriderandlib::DiscreteDistribution< IntType >virtual
LogNormalizer(double theta) const overriderandlib::PoissonRand< IntType >virtual
LogNormalizerGradient(double theta) const overriderandlib::PoissonRand< IntType >virtual
logP(const IntType &k) const overriderandlib::PoissonRand< IntType >virtual
LogProbabilityMassFunction(std::span< const IntType > x, std::span< double > y) constrandlib::DiscreteDistribution< IntType >
LogProbabilityMeasure(IntType x) constrandlib::ExponentialFamily< IntType, double >
LOWER_LIMIT_VIOLATIONrandlib::ProbabilityDistribution< T >protectedstatic
MAX_ITER_REJECTIONrandlib::ProbabilityDistribution< T >protectedstatic
MaxValue() const overriderandlib::PoissonRand< IntType >inlinevirtual
Mean() const overriderandlib::PoissonRand< IntType >virtual
Median() const overriderandlib::PoissonRand< IntType >virtual
MinValue() const overriderandlib::PoissonRand< IntType >inlinevirtual
Mode() const overriderandlib::PoissonRand< IntType >virtual
Name() const overriderandlib::PoissonRand< IntType >virtual
NaturalParameters() const overriderandlib::PoissonRand< IntType >virtual
NON_NEGATIVITY_VIOLATIONrandlib::ProbabilityDistribution< T >protectedstatic
operator()(G &g) constrandlib::PoissonRand< IntType >
P(const IntType &k) constrandlib::DiscreteDistribution< IntType >inlinevirtual
PearsonChiSquaredTest(std::span< const IntType > orderStatistic, double alpha, int lowerBoundary, int upperBoundary, size_t numberOfEstimatedParameters=0) constrandlib::DiscreteDistribution< IntType >
PearsonChiSquaredTest(std::span< const IntType > orderStatistic, double alpha, size_t numberOfEstimatedParameters=0) constrandlib::DiscreteDistribution< IntType >
PoissonRand(double rate=1.0)randlib::PoissonRand< IntType >explicit
POSITIVITY_VIOLATIONrandlib::ProbabilityDistribution< T >protectedstatic
ProbabilityDistribution()=defaultrandlib::ProbabilityDistribution< T >protected
ProbabilityMassFunction(std::span< const IntType > x, std::span< double > y) constrandlib::DiscreteDistribution< IntType >
ProbabilityMeasure(IntType x) constrandlib::ExponentialFamily< IntType, double >
Quantile(double p) constrandlib::UnivariateDistribution< IntType >
Quantile1m(double p) constrandlib::UnivariateDistribution< IntType >
QuantileFunction(std::span< const double > p, std::span< IntType > y) constrandlib::UnivariateDistribution< IntType >
QuantileFunction1m(std::span< const double > p, std::span< IntType > y) constrandlib::UnivariateDistribution< IntType >
quantileImpl(double p, IntType initValue) const overriderandlib::DiscreteDistribution< IntType >protectedvirtual
quantileImpl(double p) const overriderandlib::DiscreteDistribution< IntType >protectedvirtual
quantileImpl1m(double p, IntType initValue) const overriderandlib::DiscreteDistribution< IntType >protectedvirtual
quantileImpl1m(double p) const overriderandlib::DiscreteDistribution< IntType >protectedvirtual
Reseed(std::uint64_t seed)randlib::ProbabilityDistribution< T >inline
S(const IntType &k) const overriderandlib::PoissonRand< IntType >
randlib::DiscreteDistribution::S(const T &x) constrandlib::ProbabilityDistribution< T >virtual
randlib::DiscreteDistribution::sample(detail::EngineRef g, std::span< T > outputData) constrandlib::ProbabilityDistribution< T >inlineprotectedvirtual
Sample(std::span< T > outputData) constrandlib::ProbabilityDistribution< T >inline
Sample(G &g, std::span< T > outputData) constrandlib::ProbabilityDistribution< T >inline
SecondMoment() constrandlib::UnivariateDistribution< IntType >virtual
SetRate(double rate)randlib::PoissonRand< IntType >
Skewness() const overriderandlib::PoissonRand< IntType >virtual
SourceParameters() const overriderandlib::PoissonRand< IntType >virtual
SourceToNatural(double sourceParameters) const overriderandlib::PoissonRand< IntType >virtual
SufficientStatistic(IntType x) const overriderandlib::PoissonRand< IntType >virtual
SupportType() const overriderandlib::PoissonRand< IntType >inlinevirtual
SurvivalFunction(std::span< const T > x, std::span< double > y) constrandlib::ProbabilityDistribution< T >
ThirdMoment() constrandlib::UnivariateDistribution< IntType >virtual
toStringWithPrecision(const double a_value, const int n=6) constrandlib::ProbabilityDistribution< T >protected
UnivariateDistribution()randlib::UnivariateDistribution< IntType >protected
UPPER_LIMIT_VIOLATIONrandlib::ProbabilityDistribution< T >protectedstatic
value_type typedefrandlib::ProbabilityDistribution< T >
Variance() const overriderandlib::PoissonRand< IntType >virtual
Variate(double rate, G &g)randlib::PoissonRand< IntType >static
randlib::DiscreteDistribution::Variate() constrandlib::ProbabilityDistribution< T >inline
~DiscreteDistribution()randlib::DiscreteDistribution< IntType >inlinevirtual
~ExponentialFamily()randlib::ExponentialFamily< IntType, double >inlinevirtual
~ProbabilityDistribution()=defaultrandlib::ProbabilityDistribution< T >virtual
~UnivariateDistribution()randlib::UnivariateDistribution< IntType >inlinevirtual