rice_moore function

Rice and Moore's method

Calculate a binomial series lower confidence bound using Rice and Moore's (1983) method.

rice_moore(s, n, alpha, MonteCarlo, f.star = 1.5 - min(n) + 0.5 * sqrt((3 - 2
  * min(n))^2 - 4 * (min(n) - 1) * log(alpha) * qchisq(p = alpha, df = 2)), ...)

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.
• f.star: The number of psuedo-failures to use for a component that exhibits zero observed failures. The default value is from the log-gamma procedure proposed by Gatliffe (1976), and is the value used by Rice and Moore.
• ...: Additional arguments to be ignored.

Returns

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

Examples

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