dist_beta: Beta Distribution

In reservr: Fit Distributions and Neural Networks to Censored and Truncated Data

Beta Distribution

Description

See stats::Beta

Usage

dist_beta(shape1 = NULL, shape2 = NULL, ncp = NULL)

Arguments

shape1	First scalar shape parameter, or NULL as a placeholder.
shape2	Second scalar shape parameter, or NULL as a placeholder.
ncp	Scalar non-centrality parameter, or NULL as a placeholder.

Details

All parameters can be overridden with with_params = list(shape = ..., scale = ...).

Value

A BetaDistribution object.

See Also

Other Distributions: Distribution, dist_bdegp(), dist_binomial(), dist_blended(), dist_dirac(), dist_discrete(), dist_empirical(), dist_erlangmix(), dist_exponential(), dist_gamma(), dist_genpareto(), dist_lognormal(), dist_mixture(), dist_negbinomial(), dist_normal(), dist_pareto(), dist_poisson(), dist_translate(), dist_trunc(), dist_uniform(), dist_weibull()

Examples

d_beta <- dist_beta(shape1 = 2, shape2 = 2, ncp = 0)
x <- d_beta$sample(100)
d_emp <- dist_empirical(x)

plot_distributions(
  empirical = d_emp,
  theoretical = d_beta,
  estimated = d_beta,
  with_params = list(
    estimated = inflate_params(
      fitdistrplus::fitdist(x, distr = "beta")$estimate
    )
  ),
  .x = seq(0, 2, length.out = 100)
)

reservr documentation built on June 24, 2024, 5:10 p.m.