B1prop: Bayesian analysis of the binomial parameter for one sample.

In evidence: Analysis of Scientific Evidence Using Bayesian and Likelihood Methods

Description

This function computes the posterior distribution of the binomial probability π 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 π.

Usage

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

Value

the posterior probability

Author(s)

Robert van Hulst

References

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

See Also

B2props

prop.test

Examples

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

evidence documentation built on May 2, 2019, 2:14 p.m.