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| author | ziejd2 | 2017-09-28 15:04:40 -0500 |
|---|---|---|
| committer | ziejd2 | 2017-09-28 15:04:40 -0500 |
| commit | 8070dc963753142bb86c4ed698d91fd623ed28e7 (patch) | |
| tree | d0f6dd8fc46a49b819aa55c1a90faa14d8448883 /sourcecodes/bnt-master/nethelp3.3/demhmc1.htm | |
| parent | 7cc31810d53176e805532b2789955f4eedbce6bb (diff) | |
| download | BNW-8070dc963753142bb86c4ed698d91fd623ed28e7.tar.gz | |
BNW using Octave instead of Matlab.
This version of BNW should perform the same as the original version. The only difference is that it uses Octave instead of Matlab when running BayesNet Toolbox during parameter learning. I am calling this BNW_1.02. It can be accessed at: compbio.uthsc.edu/BNW_1.02
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diff --git a/sourcecodes/bnt-master/nethelp3.3/demhmc1.htm b/sourcecodes/bnt-master/nethelp3.3/demhmc1.htm new file mode 100644 index 00000000..4ad8b73b --- /dev/null +++ b/sourcecodes/bnt-master/nethelp3.3/demhmc1.htm @@ -0,0 +1,41 @@ +<html> +<head> +<title> +Netlab Reference Manual demhmc1 +</title> +</head> +<body> +<H1> demhmc1 +</H1> +<h2> +Purpose +</h2> +Demonstrate Hybrid Monte Carlo sampling on mixture of two Gaussians. + +<p><h2> +Synopsis +</h2> +<PRE> +demhmc1</PRE> + + +<p><h2> +Description +</h2> +The problem consists of generating data from a mixture of two Gaussians +in two dimensions using a hybrid Monte Carlo algorithm with persistence. +A mixture model is then fitted to the sample to compare it with the +true underlying generator. + +<p><h2> +See Also +</h2> +<CODE><a href="demhmc3.htm">demhmc3</a></CODE>, <CODE><a href="hmc.htm">hmc</a></CODE>, <CODE><a href="dempot.htm">dempot</a></CODE>, <CODE><a href="demgpot.htm">demgpot</a></CODE><hr> +<b>Pages:</b> +<a href="index.htm">Index</a> +<hr> +<p>Copyright (c) Ian T Nabney (1996-9) + + +</body> +</html> \ No newline at end of file |