<?xml version="1.0" encoding="shift_jis"?>
<!-- $Revision: 1.7.4.5 $  $Date: 2006/12/15 19:29:56 $ -->
<demos>
   <name>Statistics</name>
   <type>toolbox</type>
   <icon>$toolbox/matlab/icons/matlabicon.gif</icon>
   <description isCdata="no">
     <p>The Statistics Toolbox provides engineers, scientists, researchers,financial analysts, and statisticians with a comprehensive set of tools toassess and understand their data. It includes functions and interactive toolsfor analyzing historical data, modeling data, simulating systems, developingstatistical algorithms, and learning and teaching statistics.</p>
</description>

<demosection><label>Probability Distributions</label>
   <demoitem>
      <label>Distribution Functions</label>
      <type>M-GUI</type>
      <source>disttool</source>
   </demoitem>
   <demoitem>
      <label>Random Number Generation</label>
      <type>M-GUI</type>
      <source>randtool</source>
   </demoitem>
   <demoitem>
      <label>Simulating Dependent Random Variables Using Copulas</label>
      <type>M-file</type>
      <source>copulademo</source>
   </demoitem>
</demosection>


<demosection><label>Fitting Distributions to Data</label>
   <demoitem>
      <label>Analyzing Survival or Reliability Data</label>
      <type>M-file</type>
      <source>survivaldemo</source>
   </demoitem>
   <demoitem>
      <label>Fitting Custom Univariate Distributions</label>
      <type>M-file</type>
      <source>customdist1demo</source>
   </demoitem>
   <demoitem>
      <label>Fitting Custom Univariate Distributions, Part 2</label>
      <type>M-file</type>
      <source>customdist2demo</source>
   </demoitem>
   <demoitem>
      <label>Modelling Tail Data with the Generalized Pareto Distribution</label>
      <type>M-file</type>
      <source>gparetodemo</source>
   </demoitem>
   <demoitem>
      <label>Modelling Data with the Generalized Extreme Value Distribution</label>
      <type>M-file</type>
      <source>gevdemo</source>
   </demoitem>
   <demoitem>
      <label>Curve Fitting and Distribution Fitting</label>
      <type>M-file</type>
      <source>cfitdfitdemo</source>
   </demoitem>
   <demoitem>
      <label>Fitting a Univariate Distribution Using Cumulative Probabilities</label>
      <type>M-file</type>
      <source>cdffitdemo</source>
   </demoitem>
</demosection>


<demosection><label>Multivariate Analysis</label>
   <demoitem>
      <label>Visualizing Multivariate Data</label>
      <type>M-file</type>
      <source>mvplotdemo</source>
   </demoitem>
   <demoitem>
      <label>Classification</label>
      <type>M-file</type>
      <source>classdemo</source>
   </demoitem>
   <demoitem>
      <label>Cluster Analysis</label>
      <type>M-file</type>
      <source>clusterdemo</source>
   </demoitem>
   <demoitem>
      <label>Factor Analysis</label>
      <type>M-file</type>
      <source>factorandemo</source>
   </demoitem>
   <demoitem>
      <label>Classical Multidimensional Scaling</label>
      <type>M-file</type>
      <source>cmdscaledemo</source>
   </demoitem>
   <demoitem>
      <label>Non-Classical Multidimensional Scaling</label>
      <type>M-file</type>
      <source>mdscaledemo</source>
   </demoitem>
   <demoitem>
      <label>Fitting an Orthogonal Regression Using Principal Components Analysis</label>
      <type>M-file</type>
      <source>orthoregdemo</source>
   </demoitem>
</demosection>

<demosection><label>Regression</label>
   <demoitem>
      <label>Empirical Modeling</label>
      <type>M-GUI</type>
      <source>rsmdemo</source>
   </demoitem>
   <demoitem>
      <label>Fitting Data with Generalized Linear Models</label>
      <type>M-file</type>
      <source>glmdemo</source>
   </demoitem>
   <demoitem>
      <label>Bayesian Analysis for a Logistic Regression Model</label>
      <type>M-file</type>
      <source>bayesdemo</source>
   </demoitem>
   <demoitem>
      <label>Polynomial Fitting</label>
      <type>M-GUI</type>
      <source>polytool</source>
      <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>
      <type>M-GUI</type>
      <source>robustdemo</source>
   </demoitem>
   <demoitem>
      <label>Time Series Regression of Airline Passenger Data</label>
      <type>M-file</type>
      <source>stattsdemo</source>
   </demoitem>
   <demoitem>
      <label>Weighted Nonlinear Regression</label>
      <type>M-file</type>
      <source>wnlsdemo</source>
   </demoitem>
   <demoitem>
      <label>Pitfalls in Fitting Nonlinear Models by Transforming to Linearity</label>
      <type>M-file</type>
      <source>xform2lineardemo</source>
   </demoitem>
</demosection>


<demosection><label>Hypothesis Testing</label>
   <demoitem>
      <label>Selecting a Sample Size</label>
      <type>M-file</type>
      <source>samplesizedemo</source>
   </demoitem>
</demosection>

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

</demos>
