📄 sar_d3.m
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% PURPOSE: An example of using sar on a large data set
% Gibbs sampling spatial autoregressive model
%---------------------------------------------------
% USAGE: sar_d3 (see sar_d for a small data set)
%---------------------------------------------------
clear all;
n = 3107;
% NOTE a large data set with 3107 observations
% from Pace and Barry, takes around 150-250 seconds
load elect.dat; % load data on votes
y = log(elect(:,7)./elect(:,8));
x1 = log(elect(:,9)./elect(:,8));
x2 = log(elect(:,10)./elect(:,8));
x3 = log(elect(:,11)./elect(:,8));
latt = elect(:,5);
long = elect(:,6);
n = length(y); x = [ones(n,1) x1 x2 x3];
clear x1; clear x2; clear x3;
clear elect; % conserve on RAM memory
[junk W junk] = xy2cont(latt,long);
vnames = strvcat('voters','const','educ','homeowners','income');
info.lflag = 0; % use full lndet calculation
result = sar(y,x,W,info); % maximum likelihood estimates
prt(result,vnames);
% use default MC approximation for lndet calculation
result2 = sar(y,x,W); % maximum likelihood estimates
prt(result2,vnames);
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