B1propSim: simulates Bayesian updating of the binomial parameter pi.

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

Description

Provides a simple demonstration of how the posterior distribution improves as increasing amounts of data become available. A Binomial variable with a known parametric probability is sampled, and as increasing numbers of samples become available the posterior distribution is re-evaluated and plotted.

Usage

B1propSim(p, N = 100, prior = c("uniform", "near_0.5",
  "not_near_0.5", "near_0", "near_1"))

Arguments

p	the “real” binomial probability; if a number samller than 0 or one lager than 1 isentered the function will choose an arbitrary probability
N	the number of observations to accumulate
prior	one of: "uniform", "near_0.5", "not_near_0.5", "near_0", or "near_1".

Value

none returned; the function is run for the plot it produces.

Author(s)

Robert van Hulst

References

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

Examples

B1propSim(p = 0.44, prior = "near_0.5")

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