See stats::Beta
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.
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)
)
#> Warning: Removed 141 rows containing missing values or values outside the scale range
#> (`geom_line()`).