Expands (sd_mult > 1
) or reduces (sd_mult < 1
) the standard deviation
of the Beta distribution. The Beta distribution has a maximum variance of
mean(x) * (1 - mean(x)
, where mean(x) = alpha / (alpha + beta)
. If the
inputs produce a desired variance that is greater than the maximum possible
variance, or provides alpha and/or beta parameters that are < 1
and thus
push more probability weight towards extreme probability values, this
function returns alpha = 1
and beta = 1
(the uniform distribution).
sens_beta(alpha, beta, sd_mult = 2)
A named list of the adjusted distribution's parameters.
Other sens_dist:
sens_exp()
,
sens_gamma()
,
sens_gamma_pois()
,
sens_gamma_pois_zi()
,
sens_lnorm()
,
sens_neg_binom()
,
sens_norm()
,
sens_pois()
,
sens_skewnorm()
,
sens_student()
sens_beta(10, 10, 2)
#> $alpha
#> [1] 2.125
#>
#> $beta
#> [1] 2.125
#>
sens_beta(10, 10, 0.8)
#> $alpha
#> [1] 15.90625
#>
#> $beta
#> [1] 15.90625
#>