Description Usage Arguments Value Author(s) Examples
Calculates the HPD interval for the probability parameter underlying a binomially distributed outcome.
1 2 | binomial_hpdi(n_successes, n_trials, prob, prior_shape1 = 1,
prior_shape2 = 1)
|
n_successes |
The number of successes. |
n_trials |
The total number of trials. |
prob |
The size of the HPDI interval with 0 < prob <= 1. |
prior_shape1 |
The shape1 parameter of the Beta distribution defining the prior. The default values shape1=1 and shape2=1 define a flat prior assigning equal probability density to all possible parameter values. |
prior_shape2 |
The shape2 parameter of the Beta distribution defining the prior. The default values shape1=1 and shape2=1 define a flat prior assigning equal probability density to all possible parameter values. |
A vector containing the endpoints of the HPDI.
Titus von der Malsburg <malsburg@uni-potsdam.de>
1 2 3 4 5 6 7 8 | # 6/9 successes with flat prior:
binomial_hpdi(6, 9, 0.8)
# 6/9 successes with prior assuming one prior success and one failure:
binomial_hpdi(6, 9, 0.8, 2, 2)
# Equivalently:
binomial_hpdi(7, 11, 0.8)
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