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<html><head> <meta HTTP-EQUIV="Content-Type" CONTENT="text/html;charset=ISO-8859-1"> <title>Contents.m</title><link rel="stylesheet" type="text/css" href="../stpr.css"></head><body><table border=0 width="100%" cellpadding=0 cellspacing=0><tr valign="baseline"><td valign="baseline" class="function"><b class="function">DSAMP</b><td valign="baseline" align="right" class="function"><a href="../probab/index.html" target="mdsdir"><img border = 0 src="../up.gif"></a></table> <p><b>Generates samples from discrete distribution.</b></p> <hr><div class='code'><code><span class=help></span><br><span class=help> <span class=help_field>Synopsis:</span></span><br><span class=help> X = dsamp(Px,num_data)</span><br><span class=help></span><br><span class=help> <span class=help_field>Input:</span></span><br><span class=help> Px [dim x 1] Discrete probability distribution; it must</span><br><span class=help> satisfy sum(Px) = 1 and min(Px) >= 0.</span><br><span class=help> num_data [1 x 1] Number of samples to be generated.</span><br><span class=help> </span><br><span class=help> <span class=help_field>Example:</span></span><br><span class=help> Px = [0.2 0.3 0.1 0.4];</span><br><span class=help> X = dsamp(Px,1000);</span><br><span class=help> Px_emp = hist(X,4)/1000</span><br><span class=help></span><br><span class=help> See also</span><br><span class=help> GSAMP, GMMSAMP</span><br></code></div> <hr> <b>Source:</b> <a href= "../probab/list/dsamp.html">dsamp.m</a> <p><b class="info_field">About: </b> Statistical Pattern Recognition Toolbox<br> (C) 1999-2005, Written by Vojtech Franc and Vaclav Hlavac<br> Czech Technical University Prague<br> Faculty of Electrical Engineering<br> Center for Machine Perception<br> <p><b class="info_field">Modifications: </b> <br> 26-mar-2005, VF<br></body></html>?? 快捷鍵說明
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