Binomial confidence intervals using the probit parameterization

Uses the probit parameterization on the observed proportion to construct confidence intervals.

binom.probit(x, n, conf.level = 0.95, ...)

Arguments

x: Vector of number of successes in the binomial experiment.
n: Vector of number of independent trials in the binomial experiment.
conf.level: The level of confidence to be used in the confidence interval.
...: ignored

Details

For derivations see doc/binom.pdf.

Value

A data.frame containing the observed proportions and the lower and upper bounds of the confidence interval.

Author

Sundar Dorai-Raj (sdorairaj@gmail.com)

Examples

binom.probit(x = 0:10, n = 10)
#>    method  x  n mean       lower     upper
#> 1  probit  0 10  0.0 0.000000000 0.3084971
#> 2  probit  1 10  0.1 0.009615045 0.4121325
#> 3  probit  2 10  0.2 0.042069184 0.5175162
#> 4  probit  3 10  0.3 0.089913473 0.6150429
#> 5  probit  4 10  0.4 0.149339067 0.7028372
#> 6  probit  5 10  0.5 0.218639015 0.7813610
#> 7  probit  6 10  0.6 0.297162850 0.8506609
#> 8  probit  7 10  0.7 0.384957138 0.9100865
#> 9  probit  8 10  0.8 0.482483818 0.9579308
#> 10 probit  9 10  0.9 0.587867505 0.9903850
#> 11 probit 10 10  1.0 0.691502892 1.0000000