rice_moore {serieslcb} | R Documentation |
Rice and Moore's method
Description
Calculate a binomial series lower confidence bound using Rice and Moore's (1983) method.
Usage
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- |
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. |
Value
The 100(1-\alpha
)% lower confidence bound.
Examples
rice_moore(s=c(35, 97, 59), n=c(35, 100, 60), alpha=.10, MonteCarlo=1000)
[Package serieslcb version 0.4.0 Index]