Mathematical and statistical functions for the Noncentral Beta distribution, which is commonly used as the prior in Bayesian modelling.
Returns an R6 object inheriting from class SDistribution.
The distribution is supported on \([0, 1]\).
BetaNC(shape1 = 1, shape2 = 1, location = 0)
N/A
N/A
distr6::Distribution
-> distr6::SDistribution
-> BetaNoncentral
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.
new()
Creates a new instance of this R6 class.
BetaNoncentral$new( shape1 = NULL, shape2 = NULL, location = NULL, decorators = NULL )
shape1
(numeric(1))
First shape parameter, shape1 > 0
.
shape2
(numeric(1))
Second shape parameter, shape2 > 0
.
location
(numeric(1))
Location parameter, defined on the non-negative Reals.
decorators
(character())
Decorators to add to the distribution during construction.
setParameterValue()
Sets the value(s) of the given parameter(s).
BetaNoncentral$setParameterValue( ..., lst = NULL, error = "warn", resolveConflicts = FALSE )
...
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.
clone()
The objects of this class are cloneable with this method.
BetaNoncentral$clone(deep = FALSE)
deep
Whether to make a deep clone.
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.
McLaughlin, M. P. (2001). A compendium of common probability distributions (pp. 2014-01). Michael P. McLaughlin.
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