drawSamples: Simulate data from auto- models

In automultinomial: Models for Spatially Correlated Data

Description

Generates data from the autologistic and automultinomial models via Gibbs sampling. See the vignette for an example of use.

Usage

drawSamples(beta, gamma, X, A, burnIn = 300, nSamples, y = NULL)

Arguments

beta	coefficient vector (for the autologistic model) or matrix (for the automultinomial model)
gamma	the value of the autocorrelation parameter
X	the design matrix
A	the (square symmetric) adjacency matrix encoding the neighborhood structure
burnIn	the number of burnin samples to be used. Defaults to 300
nSamples	the number of samples to draw
y	optional starting configuration, in factor form. Defaults to NULL

Value

simulated samples

Examples

##########generating coefficient values and data
#adjacency matrix A
A=igraph::get.adjacency(igraph::make_lattice(c(40,40)))

#design matrix
X=cbind(rep(1,1600),matrix(rnorm(1600*4),ncol=4))

#correlation parameter
gamma=0.6

#2 response categories (1 column in coefficient matrix)
beta2=matrix(rnorm(5)*0.3,ncol=1)
#This example uses a short burnIn period. Use a longer burnIn in practice.
y2=drawSamples(beta2,gamma,X,A,burnIn=1,nSamples=1)

#3 response categories (2 columns in coefficient matrix)
beta3=matrix(rnorm(10)*0.3,ncol=2)
y3=drawSamples(beta3,gamma,X,A,burnIn=1,nSamples=1)
##########

automultinomial documentation built on May 2, 2019, 7:12 a.m.