Changeset 271 for doc/local/Intro.dox

Show
Ignore:
Timestamp:
02/16/09 10:03:13 (15 years ago)
Author:
smidl
Message:

Next major revision

Files:
1 modified

Legend:

Unmodified
Added
Removed

  • doc/local/Intro.dox

    r248 r271  
    11/*! 
    2 \page philosophy Introduction to Bayesian Decision Making Toolbox BDM 
     2\page intro Introduction to Bayesian Decision Making Toolbox BDM 
    33 
    44This is a brief introduction into elements used in the BDM. The toolbox was designed for two principle tasks: 
    … …  
    2424We make the following assumptions about data: 
    2525<ul> 
    26  <li >an individual data record is stored in a vector, \c vec \c dt,</li> 
     26 <li >an individual data record is stored in a vector, \c vec \c dt, </li> 
    2727 <li> a set of data records is stored in a matrix,\c mat \c D, where each column represent one individual data record </li> 
    2828 </ul> 
    … …  
    5757<ul> 
    5858<li> \c mpdf a pdf conditioned on another symbolic variable,</li> 
    59 <dt> \c RV a symbolic variable on which pdfs are defined.</li> 
     59<li> \c RV a symbolic variable on which pdfs are defined.</li> 
    6060</ul> 
    6161The former class is an extension of mpdf that allows conditioning on a symbolic variable. Hence, when numerical results - such as samples -  are required, numericla values of the condition must be provided. The names of methods of the \c epdf are used extended by suffix \c cond, i.e. \c samplecond(), \c evallogcond(), where \c cond precedes matrix estension, i.e. \c samplecond_m() and \c evallogcond_m().