<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision: 1.7.4.2 $  $Date: 2004/03/22 23:55:01 $ -->
<demos>
   <name>Statistics</name>
   <type>toolbox</type>
   <icon>$toolbox/matlab/icons/matlabicon.gif</icon>
   <description>
&lt;title&gt;Statistics Demos&lt;/title&gt;

&lt;p&gt;The Statistics Toolbox is a collection of MATLAB functions for
descriptive, inferential, and graphical statistics, probability modeling, and
random number generation. The toolbox includes several interactive graphic
environments for dynamic visualization of data, functions, and probability
distributions.&lt;/p&gt;
</description>

<demosection><label>Probability Distributions</label>
   <demoitem>
      <label>Distribution Functions</label>
      <callback>disttool</callback>
   </demoitem>
   <demoitem>
      <label>Random Number Generation</label>
      <callback>randtool</callback>
   </demoitem>
   <demoitem>
      <label>Simulating Dependent Random Variables Using Copulas</label>
      <file>html/copulademo.html</file>
   </demoitem>
</demosection>


<demosection><label>Fitting Distributions to Data</label>
   <demoitem>
      <label>Survival Analysis</label>
      <file>html/survivaldemo.html</file>
   </demoitem>
   <demoitem>
      <label>Fitting Custom Univariate Distributions</label>
      <file>html/customdist1demo.html</file>
   </demoitem>
   <demoitem>
      <label>Fitting Custom Univariate Distributions, Part 2</label>
      <file>html/customdist2demo.html</file>
   </demoitem>
   <demoitem>
      <label>Modeling the Tails of a Distribution</label>
      <file>html/gparetodemo.html</file>
   </demoitem>
</demosection>


<demosection>
   <label>Multivariate Analysis</label>

   <demoitem>
      <label>Visualizing Multivariate Data</label>
      <file>html/mvplotdemo.html</file>
   </demoitem>
   <demoitem>
      <label>Classification</label>
      <file>html/classdemo.html</file>
   </demoitem>
   <demoitem>
      <label>Cluster Analysis</label>
      <file>html/clusterdemo.html</file>
   </demoitem>
   <demoitem>
      <label>Factor Analysis</label>
      <file>html/factorandemo.html</file>
   </demoitem>
   <demoitem>
      <label>Classical Multidimensional Scaling</label>
      <file>html/cmdscaledemo.html</file>
   </demoitem>
   <demoitem>
      <label>Non-Classical Multidimensional Scaling</label>
      <file>html/mdscaledemo.html</file>
   </demoitem>
</demosection>

<demosection><label>Regression</label>
   <demoitem>
      <label>Empirical Modeling</label>
      <callback>rsmdemo</callback>
   </demoitem>
   <demoitem>
      <label>Generalized Linear Models</label>
      <file>html/glmdemo.html</file>
   </demoitem>
   <demoitem>
      <label>Polynomial Fitting</label>
      <callback>polytool((1:10)',[ones(10,1) (1:10)' (1:10)'.*(1:10)']*[50;4;-0.75]+randn(10,1))';</callback>
   </demoitem>
   <demoitem>
      <label>Robust Regression</label>
      <callback>robustdemo</callback>
   </demoitem>
</demosection>


<demosection><label>Hypothesis Testing</label>
   <demoitem>
      <label>Selecting a Sample Size</label>
      <file>html/samplesizedemo.html</file>
   </demoitem>
</demosection>

<demosection><label>Plotting</label>
   <demoitem>
      <label>Interactive Contour Plots</label>
      <callback>fsurfht('peaks',[-3 3],[-3 3])</callback>
   </demoitem>
</demosection>

</demos>
