findPostMean {bayesloglin}R Documentation

Posterior covariance matrix for a decomposable model.

Description

Computes the posterior mean, which for decomposable models, is known in closed form.

Usage

findPostMean(formula, alpha, data)

Arguments

formula

A decomposable model formula.

alpha

The value of the hyperparameter alpha.

data

A data frame containing the contingency table. All cells must be included in data and the last column must be the cell counts. The number of variables in the contingency table must be at least 2.

Value

theta

An array giving the posterior mean of the log-linear parameters.

Author(s)

Matthew Friedlander

References

see vignette

Examples

data(czech)
formula <- freq ~ b*c + a*c*e + d*e + f
s <- findPostMean (formula, alpha = 1, data = czech)
print(s)

[Package bayesloglin version 1.0.1 Index]