dga (version 2.0.1)

CompLogML: Computes Marginal Likelihoods for Each Clique and Value of Nmissing

Description

Assembles all of the pieces of the marginal likelihoods to be used to calculate the posterior probability of each model/value of Nmissing.

Usage

CompLogML(D, Nmissing, delta)

Value

The log marginal likelihood of the marginal table.

Arguments

D

A marginal array of the list overlap counts.

Nmissing

The vector of possible values for the missing cell.

delta

The prior hyper parameter for the Dirichlet distribution.

Author

James Johndrow and Kristian Lum

References

Madigan, David, and Jeremy C. York. "Bayesian methods for estimation of the size of a closed population." Biometrika 84.1 (1997): 19-31.

Examples

Y <- c(0, 27, 37, 19, 4, 4, 1, 1, 97, 22, 37, 25, 2, 1, 3, 5,
       83, 36, 34, 18, 3, 5, 0, 2, 30, 5, 23, 8, 0, 3, 0, 2)
Y <- array(Y, dim = c(2, 2, 2, 2, 2))

# Compute marginal array over lists 1 and 3
D <- apply(Y, c(1, 3), sum)

dga:::CompLogML(D, 1:300, 0.5)