| Type: | Package |
| Title: | Blyth-Still-Casella Confidence Interval |
| Version: | 0.1.1 |
| Date: | 2024-01-29 |
| 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>. |
| License: | GPL (≥ 3) |
| Imports: | Rcpp |
| LinkingTo: | Rcpp, BH |
| RoxygenNote: | 6.0.1 |
| Suggests: | testthat |
| NeedsCompilation: | yes |
| Packaged: | 2024-01-29 12:21:52 UTC; stigler |
| Author: | Shimeng Huang [aut, cre], Keith Winstein [aut] |
| Maintainer: | Shimeng Huang <dora.huang.sunshine@gmail.com> |
| Repository: | CRAN |
| Date/Publication: | 2024-01-29 13:50:06 UTC |
Blyth-Still-Casella Confidence Interval
Description
Blyth-Still-Casella Confidence Interval
Details
Provides a fast calculation of the Blyth-Still-Casella confidence interval.
Blyth-Still-Casella confidence interval
Description
Blyth-Still-Casella confidence interval
Usage
bscCI(n_tot, n_suc, conf, digits = 2)
Arguments
n_tot |
Total number of experiments |
n_suc |
Number of successes |
conf |
Confidence level (1-alpha) |
digits |
Number of decimal places to be used |
Details
Computes the exact Blyth-Still-Casella binomial confidence interval. The initial CI is the Clopper-Pearson confidence interval.
Value
A vector containing the confidence interval. If digits is given, both upper and lower limits are rounded to the given number of digits.
Examples
bscCI(100,25,0.95,digits = 3)
Clopper-Pearson confidence interval
Description
Clopper-Pearson confidence interval
Usage
cpCI(n_tot, n_suc, conf, digits = 2)
Arguments
n_tot |
Total number of experiments |
n_suc |
Number of successes |
conf |
Confidence level (1-alpha) |
digits |
Number of decimal places to be used |
Details
Computes the Clopper-Pearson confidence interval.
Examples
cpCI(100,25,0.95)