![]() ![]() Which is the Monte Carlo average of the purple curve, i.e., theĪpproximation to the predictive density for the next point. The current mixture of two Gaussians (purple curve)Īfter a few iterations have elapsed a fourth curve is displayed in green,.The current two Gaussians (yellow and orange curves) The data (13 points in blue at the bottom)Īssignments of those points to the two clusters (shown by yellow and orange points).In order to view another option with the correct defaults.įor the first few iterations, the following objects are displayed: After viewing one option, you may find it necessary to quit and restart the demonstration.single-gaussian inference silly data N=13, and Options single-gaussian inference gibbs sampling, (Works fine with octave-2.0 but not with octave-2.1.33, which seems to (Execute this command on the machine running X windows.) Modify your X windows defaults so that the gnuplot colours and fontsĬome out right. ![]() [If there are any complaints about the clock time use ![]() Tar xvf gibbsdemo.tar This unpacks a load of files into a directoryĬalled gibbsdemo. If you have not got gnuplot, I recommend you install cygwinĬd ~/octave tar cvfh ~/pub/itprnn/code/gibbsdemo/gibbsdemo.tar gibbsdemo/ If you have got gnuplot on some other system (eg cygwin under Windoze), This demonstration should work if you are running X-windows on a Inferring the (mu,sigma) of Gaussian distributions using Gibbs Sampling Inferring the (mu,sigma) of a Gaussian distribution, or a mixture of Gaussians, using Gibbs Sampling ![]()
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