Function reference • distr6

Distributions Functions for Distribution constructor and helpers.
`Distribution`	Generalised Distribution Object
`SDistribution`	Abstract Special Distribution Class
`Kernel`	Abstract Kernel Class
`exkurtosisType()`	Kurtosis Type
`skewType()`	Skewness Type
`liesInSupport()`	Test if Data Lies in Distribution Support
`liesInType()`	Test if Data Lies in Distribution Type
`isCdf`	Test the Distribution Cdf Exist?
`isPdf`	Test the Distribution Pdf Exist?
`isQuantile`	Test the Distribution Quantile Exist?
`isRand`	Test the Distribution Rand Exist?
Mathematical and Statistical Mathematical and statistical functions acting on Distribution objects.
`cdf()`	Cumulative Distribution Function
`cdfAntiDeriv()`	Cumulative Distribution Function Anti-Derivative
`cdfPNorm()`	Cumulative Distribution Function P-Norm
`cf()`	Characteristic Function
`correlation()`	Distribution Correlation
`cumHazard()`	Cumulative Hazard Function
`entropy()`	Distribution Entropy
`genExp()`	Generalised Expectation of a Distribution
`generalPNorm()`	Generalised P-Norm
`hazard()`	Hazard Function
`kthmoment()`	Kth Moment
`kurtosis()`	Distribution Kurtosis
`mean(<Distribution>)`	Distribution Mean
`median(<Distribution>)`	Median of a Distribution
`mgf()`	Moment Generating Function
`mode()`	Mode of a Distribution
`pdf()`	Probability Density/Mass Function
`pdfPNorm()`	Probability Density Function P-Norm
`pgf()`	Probability Generating Function
`prec()`	Precision of a Distribution
`quantile(<Distribution>)`	Inverse Cumulative Distribution Function
`rand()`	Random Simulation Function
`simulateEmpiricalDistribution()`	Sample Empirical Distribution Without Replacement
`stdev()`	Standard Deviation of a Distribution
`skewness()`	Distribution Skewness
`skewnessType()`	Type of Skewness Accessor
`squared2Norm()`	Squared Probability Density Function 2-Norm
`survival()`	Survival Function
`survivalAntiDeriv()`	Survival Function Anti-Derivative
`survivalPNorm()`	Survival Function P-Norm
`variance()`	Distribution Variance
Distribution Accessors Accessor methods for Distribution objects.
`decorators()`	Decorators Accessor
`dmax()`	Distribution Maximum Accessor
`dmin()`	Distribution Minimum Accessor
`inf()`	Infimum Accessor
`iqr()`	Distribution Interquartile Range
`kurtosisType()`	Type of Kurtosis Accessor
`parameters()`	Parameters Accessor
`properties()`	Properties Accessor
`strprint()`	String Representation of Print
`summary(<Distribution>)`	Distribution Summary
`sup()`	Supremum Accessor
`support()`	Support Accessor
`symmetry()`	Symmetry Accessor
`traits()`	Traits Accessor
`type()`	Type Accessor
`valueSupport()`	Value Support Accessor
`variateForm()`	Variate Form Accessor
Decorators Decorators for extending functionality of distributions with numerical calculations.
`DistributionDecorator`	Abstract DistributionDecorator Class
`CoreStatistics`	Core Statistical Methods for Distributions
`ExoticStatistics`	Exotic Statistical Methods for Distributions
`FunctionImputation`	Imputed Pdf/Cdf/Quantile/Rand Functions
`decorate()`	Decorate Distributions
`listDecorators()`	Lists Implemented Distribution Decorators
Wrappers Functionality for composite modelling including joint and conditional distributions.
`DistributionWrapper`	Abstract DistributionWrapper Class
`wrappedModels()`	Gets Internally Wrapped Models
`ProductDistribution`	Product Distribution
`VectorDistribution`	Vectorise Distributions
`Extract.VectorDistribution()` `[`(<VectorDistribution>)	Extract one or more Distributions from a VectorDistribution
`c(<Distribution>)`	Combine Distributions into a VectorDistribution
`HuberizedDistribution`	Distribution Huberization Wrapper
`huberize()`	Huberize a Distribution
`TruncatedDistribution`	Distribution Truncation Wrapper
`truncate()`	Truncate a Distribution
`MixtureDistribution`	Mixture Distribution Wrapper
`Convolution`	Distribution Convolution Wrapper
Univariate Discrete Distributions
`Bernoulli`	Bernoulli Distribution Class
`Binomial`	Binomial Distribution Class
`Categorical`	Categorical Distribution Class
`Degenerate`	Degenerate Distribution Class
`DiscreteUniform`	Discrete Uniform Distribution Class
`Empirical`	Empirical Distribution Class
`Geometric`	Geometric Distribution Class
`Hypergeometric`	Hypergeometric Distribution Class
`Logarithmic`	Logarithmic Distribution Class
`NegativeBinomial`	Negative Binomial Distribution Class
`Poisson`	Poisson Distribution Class
`WeightedDiscrete`	WeightedDiscrete Distribution Class
Univariate Continuous Distributions
`Arcsine`	Arcsine Distribution Class
`Beta`	Beta Distribution Class
`BetaNoncentral`	Noncentral Beta Distribution Class
`Cauchy`	Cauchy Distribution Class
`ChiSquared`	Chi-Squared Distribution Class
`ChiSquaredNoncentral`	Noncentral Chi-Squared Distribution Class
`Exponential`	Exponential Distribution Class
`FDistribution`	'F' Distribution Class
`FDistributionNoncentral`	Noncentral F Distribution Class
`Frechet`	Frechet Distribution Class
`Gamma`	Gamma Distribution Class
`Gompertz`	Gompertz Distribution Class
`Gumbel`	Gumbel Distribution Class
`InverseGamma`	Inverse Gamma Distribution Class
`Laplace`	Laplace Distribution Class
`Logistic`	Logistic Distribution Class
`Loglogistic`	Log-Logistic Distribution Class
`Lognormal`	Log-Normal Distribution Class
`Normal`	Normal Distribution Class
`Pareto`	Pareto Distribution Class
`Rayleigh`	Rayleigh Distribution Class
`StudentT`	Student's T Distribution Class
`StudentTNoncentral`	Noncentral Student's T Distribution Class
`Triangular`	Triangular Distribution Class
`Uniform`	Uniform Distribution Class
`Wald`	Wald Distribution Class
`Weibull`	Weibull Distribution Class
Multivariate Distributions
`Dirichlet`	Dirichlet Distribution Class
`Multinomial`	Multinomial Distribution Class
`MultivariateNormal`	Multivariate Normal Distribution Class
Kernels
`Cosine`	Cosine Kernel
`Epanechnikov`	Epanechnikov Kernel
`NormalKernel`	Normal Kernel
`LogisticKernel`	Logistic Kernel
`TriangularKernel`	Triangular Kernel
`UniformKernel`	Uniform Kernel
`Quartic`	Quartic Kernel
`Sigmoid`	Sigmoid Kernel
`Silverman`	Silverman Kernel
`Tricube`	Tricube Kernel
`Triweight`	Triweight Kernel
Visualisation
`plot(<Distribution>)`	Plot Distribution Functions for a distr6 Object
`lines(<Distribution>)`	Superimpose Distribution Functions Plots for a distr6 Object
`qqplot()`	Quantile-Quantile Plots for distr6 Objects
Assertions Validation checks for Distributions.
`testContinuous()` `checkContinuous()` `assertContinuous()`	assert/check/test/Continuous
`testDiscrete()` `checkDiscrete()` `assertDiscrete()`	assert/check/test/Discrete
`testDistribution()` `checkDistribution()` `assertDistribution()`	assert/check/test/Distribution
`testDistributionList()` `checkDistributionList()` `assertDistributionList()`	assert/check/test/DistributionList
`testLeptokurtic()` `checkLeptokurtic()` `assertLeptokurtic()`	assert/check/test/Leptokurtic
`testMatrixvariate()` `checkMatrixvariate()` `assertMatrixvariate()`	assert/check/test/Matrixvariate
`testMesokurtic()` `checkMesokurtic()` `assertMesokurtic()`	assert/check/test/Mesokurtic
`testMixture()` `checkMixture()` `assertMixture()`	assert/check/test/Mixture
`testMultivariate()` `checkMultivariate()` `assertMultivariate()`	assert/check/test/Multivariate
`testNegativeSkew()` `checkNegativeSkew()` `assertNegativeSkew()`	assert/check/test/NegativeSkew
`testNoSkew()` `checkNoSkew()` `assertNoSkew()`	assert/check/test/NoSkew
`testPlatykurtic()` `checkPlatykurtic()` `assertPlatykurtic()`	assert/check/test/Platykurtic
`testPositiveSkew()` `checkPositiveSkew()` `assertPositiveSkew()`	assert/check/test/PositiveSkew
`testSymmetric()` `checkSymmetric()` `assertSymmetric()`	assert/check/test/Symmetric
`testUnivariate()` `checkUnivariate()` `assertUnivariate()`	assert/check/test/Univariate
Helper Functions Miscellaneous functions for use in distr6.
`makeUniqueDistributions()`	De-Duplicate Distribution Names
`listDistributions()`	Lists Implemented Distributions
`listKernels()`	Lists Implemented Kernels
`listWrappers()`	Lists Implemented Distribution Wrappers
`distr6-package`	distr6: Object Oriented Distributions in R
`distr6News()`	Show distr6 NEWS.md File
`distrSimulate()`	Simulate from a Distribution
Parameter Sets Functions and classes for creating Parameter Sets for use in Distributions.
`ParameterSet`	Make an R6 Parameter Set for Distributions
`as.ParameterSet()`	Coerce to a ParameterSet
`getParameterSupport()`	Parameter Support Accessor
`getParameterValue()`	Parameter Value Accessor
`setParameterValue()`	Parameter Value Setter
`as.data.table(<ParameterSet>)`	Coerce ParameterSet to data.table
`print(<ParameterSet>)`	Print a ParameterSet
`merge(<ParameterSet>)`	Combine ParameterSets
`update(<ParameterSet>)`	Updates a ParameterSet

Reference

Distributions

Mathematical and Statistical

Distribution Accessors

Decorators

Wrappers

Univariate Discrete Distributions

Univariate Continuous Distributions

Multivariate Distributions

Kernels

Visualisation

Assertions

Helper Functions

Parameter Sets