Learn R Programming

distr6 (version 1.5.2)

BetaNoncentral: Noncentral Beta Distribution Class

Description

Mathematical and statistical functions for the Noncentral Beta distribution, which is commonly used as the prior in Bayesian modelling.

Arguments

Value

Returns an R6 object inheriting from class SDistribution.

Distribution support

The distribution is supported on \([0, 1]\).

Default Parameterisation

BetaNC(shape1 = 1, shape2 = 1, location = 0)

Omitted Methods

N/A

Also known as

N/A

Super classes

distr6::Distribution -> distr6::SDistribution -> BetaNoncentral

Public fields

name

Full name of distribution.

short_name

Short name of distribution for printing.

description

Brief description of the distribution.

packages

Packages required to be installed in order to construct the distribution.

Methods

Public methods

Method new()

Creates a new instance of this R6 class.

Usage

BetaNoncentral$new(
  shape1 = NULL,
  shape2 = NULL,
  location = NULL,
  decorators = NULL
)

Arguments

shape1

(numeric(1)) First shape parameter, shape1 > 0.

shape2

(numeric(1)) Second shape parameter, shape2 > 0.

location

(numeric(1)) Location parameter, defined on the non-negative Reals.

decorators

(character()) Decorators to add to the distribution during construction.

Method setParameterValue()

Sets the value(s) of the given parameter(s).

Usage

BetaNoncentral$setParameterValue(
  ...,
  lst = NULL,
  error = "warn",
  resolveConflicts = FALSE
)

Arguments

...

ANY Named arguments of parameters to set values for. See examples.

lst

(list(1)) Alternative argument for passing parameters. List names should be parameter names and list values are the new values to set.

error

(character(1)) If "warn" then returns a warning on error, otherwise breaks if "stop".

resolveConflicts

(logical(1)) If FALSE (default) throws error if conflicting parameterisations are provided, otherwise automatically resolves them by removing all conflicting parameters.

Method clone()

The objects of this class are cloneable with this method.

Usage

BetaNoncentral$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Details

The Noncentral Beta distribution parameterised with two shape parameters, \(\alpha, \beta\), and location, \(\lambda\), is defined by the pdf, $$f(x) = exp(-\lambda/2) \sum_{r=0}^\infty ((\lambda/2)^r/r!) (x^{\alpha+r-1}(1-x)^{\beta-1})/B(\alpha+r, \beta)$$ for \(\alpha, \beta > 0, \lambda \ge 0\), where \(B\) is the Beta function.

References

McLaughlin, M. P. (2001). A compendium of common probability distributions (pp. 2014-01). Michael P. McLaughlin.

See Also

Other continuous distributions: Arcsine, Beta, Cauchy, ChiSquaredNoncentral, ChiSquared, Dirichlet, Erlang, Exponential, FDistributionNoncentral, FDistribution, Frechet, Gamma, Gompertz, Gumbel, InverseGamma, Laplace, Logistic, Loglogistic, Lognormal, MultivariateNormal, Normal, Pareto, Poisson, Rayleigh, ShiftedLoglogistic, StudentTNoncentral, StudentT, Triangular, Uniform, Wald, Weibull

Other univariate distributions: Arcsine, Bernoulli, Beta, Binomial, Categorical, Cauchy, ChiSquaredNoncentral, ChiSquared, Degenerate, DiscreteUniform, Empirical, Erlang, Exponential, FDistributionNoncentral, FDistribution, Frechet, Gamma, Geometric, Gompertz, Gumbel, Hypergeometric, InverseGamma, Laplace, Logarithmic, Logistic, Loglogistic, Lognormal, NegativeBinomial, Normal, Pareto, Poisson, Rayleigh, ShiftedLoglogistic, StudentTNoncentral, StudentT, Triangular, Uniform, Wald, Weibull, WeightedDiscrete