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