bayes_jeffreys function

Bayesian method (Jeffrey's prior)

Calculate a binomial series lower confidence bound using Bayes' method with Jeffrey's prior.

bayes_jeffreys(s, n, alpha, MonteCarlo, ...)

Arguments

• s: Vector of successes.
• n: Vector of sample sizes.
• alpha: The significance level; to calculate a 100(1-$\alpha$)% lower confidence bound.
• MonteCarlo: Number of samples to draw from the posterior distribution for the Monte Carlo estimate.
• ...: Additional arguments to be ignored.

Returns

The 100(1-$\alpha$)% lower confidence bound.

Examples

bayes_jeffreys(s=c(35, 97, 59), n=c(35, 100, 60), alpha=.10, MonteCarlo=1000)