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author Daniel Wolff
date Fri, 19 Aug 2016 13:07:06 +0200
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Daniel@0 1 <html>
Daniel@0 2 <head>
Daniel@0 3 <title>
Daniel@0 4 Netlab Reference Manual gmmsamp
Daniel@0 5 </title>
Daniel@0 6 </head>
Daniel@0 7 <body>
Daniel@0 8 <H1> gmmsamp
Daniel@0 9 </H1>
Daniel@0 10 <h2>
Daniel@0 11 Purpose
Daniel@0 12 </h2>
Daniel@0 13 Sample from a Gaussian mixture distribution.
Daniel@0 14
Daniel@0 15 <p><h2>
Daniel@0 16 Synopsis
Daniel@0 17 </h2>
Daniel@0 18 <PRE>
Daniel@0 19 data = gmmsamp(mix, n)
Daniel@0 20 [data, label] = gmmsamp(mix, n)
Daniel@0 21 </PRE>
Daniel@0 22
Daniel@0 23
Daniel@0 24 <p><h2>
Daniel@0 25 Description
Daniel@0 26 </h2>
Daniel@0 27
Daniel@0 28 <p><CODE>data = gsamp(mix, n)</CODE> generates a sample of size <CODE>n</CODE> from a
Daniel@0 29 Gaussian mixture distribution defined by the <CODE>mix</CODE> data
Daniel@0 30 structure. The matrix <CODE>x</CODE> has <CODE>n</CODE>
Daniel@0 31 rows in which each row represents a <CODE>mix.nin</CODE>-dimensional sample vector.
Daniel@0 32
Daniel@0 33 <p><CODE>[data, label] = gmmsamp(mix, n)</CODE> also returns a column vector of
Daniel@0 34 classes (as an index 1..N) <CODE>label</CODE>.
Daniel@0 35
Daniel@0 36 <p><h2>
Daniel@0 37 See Also
Daniel@0 38 </h2>
Daniel@0 39 <CODE><a href="gsamp.htm">gsamp</a></CODE>, <CODE><a href="gmm.htm">gmm</a></CODE><hr>
Daniel@0 40 <b>Pages:</b>
Daniel@0 41 <a href="index.htm">Index</a>
Daniel@0 42 <hr>
Daniel@0 43 <p>Copyright (c) Ian T Nabney (1996-9)
Daniel@0 44
Daniel@0 45
Daniel@0 46 </body>
Daniel@0 47 </html>