B1prop function

Bayesian analysis of the binomial parameter for one sample.

This function computes the posterior distribution of the binomial probability $\pi$ when given the number of ``successes'' and the sample size, as well as one of a choice of priors. A plot of the posterior distribution is produced with the 95% credible interval of $\pi$.

B1prop(s, n, p = 0.5, alpha = 0.05, prior = c("uniform", "near_0.5",
  "not_near_0.5", "near_0", "near_1", "custom"), params = NULL)

Arguments

• s: the number of sampling units with the feature
• n: the number of sampling units examined
• p: an optional hypothesized probability
• alpha: 1 - alpha is the desired level of credibility of a credible interval
• prior: one of: "uniform", "near_0.5", "not_near_0.5", "near_0", "near_1", "custom", which are all beta distributions with appropriate parameter values. Note that if prior="custom" the following argument has to be supplied:
• params: a vector with the a and b parameters of the custom beta prior

Returns

the posterior probability

References

van Hulst, R. 2018. Evaluating Scientific Evidence. ms.

Author(s)

Robert van Hulst

See Also

B2props

prop.test

Examples

B1prop(13, 100, .1, prior="near_0")