dga (version 2.0.1)

plotPosteriorN: Plots Posterior Distribution of Nmissing

Description

Plots the model averaged posterior distribution of the total number of elements (the solid line) and the contribution to the posterior of each of the models (dotted lines)

Usage

plotPosteriorN(weights, N, main = NULL)

Arguments

weights

The output of BMAfunction.

N

N + Nmissing. Or, if you prefer, just Nmissing. The former shows the posterior distribution of the total population size; the latter shows the posterior distribution of the number of missing elements.

main

the title of the plot

Value

A plot.

Examples

# NOT RUN {
##### 5 list example from M & Y #######

delta <- .5
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))
Nmissing <- 1:300
N <- Nmissing + sum(Y)
data(graphs5)
weights <- bma.cr(Y, Nmissing, delta, graphs5)
plotPosteriorN(weights, N)


##### 3 list example from M & Y #######
Y <- c(0, 60, 49, 4, 247, 112, 142, 12)
Y <- array(Y, dim = c(2, 2, 2))

delta <- 1
a <- 13.14
b <- 55.17


Nmissing <- 1:300
N <- Nmissing + sum(Y)

logprior <- N * log(b) - (N + a) * log(1 + b) + lgamma(N + a) - lgamma(N + 1) - lgamma(a)

data(graphs3)
weights <- bma.cr(Y, Nmissing, delta, graphs3, logprior)
plotPosteriorN(weights, N)
# }