| Title: | Blyth-Still-Casella Confidence Interval |
|---|---|
| Description: | Provides a fast calculation of the Blyth-Still-Casella confidence interval. The implementation follows the 'StatXact' 9 manual (Cytel 2010) and "Refining Binomial Confidence Intervals" by George Casella (1986) <doi:10.2307/3314658>. |
| Authors: | Shimeng Huang [aut, cre], Keith Winstein [aut] |
| Maintainer: | Shimeng Huang <[email protected]> |
| License: | GPL (>= 3) |
| Version: | 0.1.0 |
| Built: | 2026-05-20 05:49:02 UTC |
| Source: | https://github.com/shimenghuang/rbscci |
Blyth-Still-Casella confidence interval
bscCI(n_tot, n_suc, conf, digits = 2)bscCI(n_tot, n_suc, conf, digits = 2)
n_tot |
Total number of experiments |
n_suc |
Number of successes |
conf |
Confidence level (1-alpha) |
digits |
Number of decimal places to be used |
Computes the exact Blyth-Still-Casella binomial confidence interval. The initial CI is the Clopper-Pearson confidence interval.
A vector containing the confidence interval. If digits is given, both upper and lower limits are rounded to the given number of digits.
bscCI(100,25,0.95,digits = 3)bscCI(100,25,0.95,digits = 3)
Clopper-Pearson confidence interval
cpCI(n_tot, n_suc, conf, digits = 2)cpCI(n_tot, n_suc, conf, digits = 2)
n_tot |
Total number of experiments |
n_suc |
Number of successes |
conf |
Confidence level (1-alpha) |
digits |
Number of decimal places to be used |
Computes the Clopper-Pearson confidence interval.
cpCI(100,25,0.95)cpCI(100,25,0.95)
Blyth-Still-Casella Confidence Interval
Provides a fast calculation of the Blyth-Still-Casella confidence interval.