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wolffd@0 1 <html>
wolffd@0 2 <head>
wolffd@0 3 <title>
wolffd@0 4 Netlab Reference Manual demgauss
wolffd@0 5 </title>
wolffd@0 6 </head>
wolffd@0 7 <body>
wolffd@0 8 <H1> demgauss
wolffd@0 9 </H1>
wolffd@0 10 <h2>
wolffd@0 11 Purpose
wolffd@0 12 </h2>
wolffd@0 13 Demonstrate sampling from Gaussian distributions.
wolffd@0 14
wolffd@0 15 <p><h2>
wolffd@0 16 Synopsis
wolffd@0 17 </h2>
wolffd@0 18 <PRE>
wolffd@0 19 demgauss
wolffd@0 20 </PRE>
wolffd@0 21
wolffd@0 22
wolffd@0 23 <p><h2>
wolffd@0 24 Description
wolffd@0 25 </h2>
wolffd@0 26
wolffd@0 27 <p><CODE>demgauss</CODE> provides a simple illustration of the generation of
wolffd@0 28 data from Gaussian distributions. It first samples from a
wolffd@0 29 one-dimensional distribution using <CODE>randn</CODE>, and then plots a
wolffd@0 30 normalized histogram estimate of the distribution using <CODE>histp</CODE>
wolffd@0 31 together with the true density calculated using <CODE>gauss</CODE>.
wolffd@0 32
wolffd@0 33 <p><CODE>demgauss</CODE> then demonstrates sampling from a Gaussian distribution
wolffd@0 34 in two dimensions. It creates a mean vector and a covariance matrix,
wolffd@0 35 and then plots contours of constant density using the function
wolffd@0 36 <CODE>gauss</CODE>. A sample of points drawn from this distribution, obtained
wolffd@0 37 using the function <CODE>gsamp</CODE>, is then superimposed on the contours.
wolffd@0 38
wolffd@0 39 <p><h2>
wolffd@0 40 See Also
wolffd@0 41 </h2>
wolffd@0 42 <CODE><a href="gauss.htm">gauss</a></CODE>, <CODE><a href="gsamp.htm">gsamp</a></CODE>, <CODE><a href="histp.htm">histp</a></CODE><hr>
wolffd@0 43 <b>Pages:</b>
wolffd@0 44 <a href="index.htm">Index</a>
wolffd@0 45 <hr>
wolffd@0 46 <p>Copyright (c) Ian T Nabney (1996-9)
wolffd@0 47
wolffd@0 48
wolffd@0 49 </body>
wolffd@0 50 </html>