Bayes.disc: Bayesian graphical summaries for discrete or categorical...

In asbio: A Collection of Statistical Tools for Biologists

Bayesian graphical summaries for discrete or categorical data.

Description

An simple function for for summarizing a Bayesian analysis given discrete or categorical variables and priors.

Usage

Bayes.disc(Likelihood, Prior, data.name = "data", plot = TRUE, 
c.data = seq(1, length(Prior)), ...)

Bayes.disc.tck()

Arguments

Likelihood	A vector of sample distribution probabilities. This must be in the same order as Prior, i.e. if \theta_1 is the first element in Prior, then data|\theta_1 must be the first element in Data.
Prior	A vector of prior probabilities, or weights.
data.name	A name for data in conditional statements.
plot	Logical, indicating whether a plot should be made.
c.data	A character string of names for discrete classes
...	Additional arguments to plot.

Author(s)

Ken Aho

asbio documentation built on May 29, 2024, 5:57 a.m.