
    \foldertitle{logdist}{Probability distribution package}{logdist/Contents}

	This package gives quick access to basic univariate distributions. Its
 primary use is setting up priors in the \url{model/estimate} and
 \url{poster/arwm} functions.
 
 The logdist package is called to create function handles that have
 several different modes of use. The primary use is to compute values
 that are proportional to the log of the respective density. In addition,
 the function handles also give you access to extra information (such as
 the the proper p.d.f., the name, mean, std dev, mode, and stuctural
 parameters of the distribution), and to a random number generator from
 the respective distribution.
 
 Logdist methods:
 
 \paragraph{Getting function handles for univariate distributions}
 
 \begin{itemize}
 \item
   \href{logdist/normal}{\texttt{normal}} - Create function proportional
   to log of normal distribution.
 \item
   \href{logdist/lognormal}{\texttt{lognormal}} - Create function
   proportional to log of log-normal distribution.
 \item
   \href{logdist/beta}{\texttt{beta}} - Create function proportional to
   log of beta distribution.
 \item
   \href{logdist/gamma}{\texttt{gamma}} - Create function proportional to
   log of gamma distribution.
 \item
   \href{logdist/invgamma}{\texttt{invgamma}} - Create function
   proportional to log of inv-gamma distribution.
 \item
   \href{logdist/uniform}{\texttt{uniform}} - Create function
   proportional to log of uniform distribution.
 \end{itemize}
 \paragraph{Calling the logdist function handles}
 
 The function handles \texttt{F} created by the logdist package functions
 can be called the following ways:
 
 \begin{itemize}
 \item
   Get a value proportional to the log-density of the respective
   distribution at a particular point; this call is used within the
   \href{poster/Contents}{posterior simulator}:
 
   y = F(x)
 \item
   Get the density of the respective distribution at a particular point:
 
   y = F(x,`pdf')
 \item
   Get the characteristics of the distribution --- mean, std deviation,
   mode, and information (the inverse of the second derivative of the log
   density):
 
   m = F({[}{]},`mean') s = F({[}{]},`std') o = F({[}{]},`mode') i =
   F({[}{]},`info')
 \item
   Get the underlying ``structural'' parameters of the respective
   distribution:
 
   a = F({[}{]},`a') b = F({[}{]},`b')
 \item
   Get the name of the distribution (the names correspond to the function
   names, i.e.~can be either of \texttt{'normal'}, \texttt{'lognormal'},
   \texttt{'beta'}, \texttt{'gamma'}, \texttt{'invgamma'},
   \texttt{'uniform'}):
 
   name = F({[}{]},`name')
 \item
   Draw a vector or matrix of random numbers from the distribution;
   drawing from beta, gamma, and inverse gamma requires the Statistics
   Toolbox:
 
   a = F({[}{]},`draw',1,1000);
 
   size(a) ans = 1 10000
 \end{itemize}
 \paragraph{Getting on-line help on logdist functions}
 
 \begin{verbatim}
 help logdist
 help logdist/function_name
 \end{verbatim}



