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\usepackage{alltt}-0.18 (-4.25%) 	28.00 	101.92 	113.68 	11.76 	11.54% 	
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\title{GUI Model}
\author{Matthew Bartenshlag, Peter Santiago}
\newcommand{\codelist}[2]{\begin{figure}%
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\begin{document}
\maketitle
\section{Defmodel Code}
\codelist{defmodelcode1}{model1.lisp}
\codelist{defmodelcode2}{model2.lisp}
\codelist{defmodelcode3}{model25.lisp}
\codelist{defmodelcode4}{model3.lisp}
\codelist{testmodel}{testmodel.lisp}
To facilitate the implementation of forensic models in Lisp, a simple modeling language
was created. While the code for the modeling language itself is lengthy and intimidating, 
the resulting modeling language is quite simple.

There are four main components to the model: a set of parameters, an equation used to
evaluate the model given the set of input parameters, a contrast set learner, and the
interface with gnuplot. 

As a side effect of the model code, two important and named functions are created. If
someone were to create a model and name it testmodel, then the defmodel macro would
create a testmodel-ui function which calls the user interface and a testmodel-model function
which would evaluate the model with the given parameters without requiring the user interface.
Figure \ref{fig:testmodel} illustrates the use of defmodel.


See Figures \ref{fig:defmodelcode1}, \ref{fig:defmodelcode2}, \ref{fig:defmodelcode3}, and \ref{fig:defmodelcode4} for code.

\clearpage
\section{Evett Model} 
\codelist{defmodelevett}{defmodelevett.lisp}
\begin{figure}
\centering
\includegraphics[width=.85\textwidth]{evett.png}
\caption{Evett GUI}
\label{evettgui}
\end{figure}
The Evett model implements the Evett algorithm described in his 1994 paper. Using this model,
observers can determine how modifications to lambda, mu, and n affect the likelihood ratio
of Evett's algorithm. The model works by calculating the likelihood ratios from n=0 to n=nvalue
and lamb=0 to lamb=lambvalue, where lambvalue and nvalue are the user-input values for
lambda and n. Also included in Evett's algorithm is an f-value. While this parameter is provided,
analysis of the model has determined that the f-value has little influence on the results.

Frequency counts and contrast set learning is not implemented for this model. This is
because real-world data for the input parameters are not readily available.

See Figure \ref{fig:defmodelevett} for code. 

A sample gui image is located in Figure \ref{evettgui}.

\clearpage
\section{Seheult Model}
\codelist{defmodelseheult1}{defmodelseheult1.lisp}
\codelist{defmodelseheult2}{defmodelseheult2.lisp}
\begin{figure}
\centering
\includegraphics[width=.85\textwidth]{seheult.png}
\caption{Seheult GUI}
\label{seheultgui}
\end{figure}
The final section of the defmodel pertaining to the generation of three-dimensional graphs has been heavily modified. This model implements the Seheult algorithm as described in (insert section reference once this is combined with the full document).  
See Figures \ref{fig:defmodelseheult1}, \ref{fig:defmodelseheult2} for code. 
A sample gui image is located in Figure \ref{seheultgui}.

\clearpage
\section{Grove Model}
\codelist{defmodelgrove1}{defmodelgrove1.lisp}
\codelist{defmodelgrove2}{defmodelgrove2.lisp}
\begin{figure}
\centering
\includegraphics[width=.85\textwidth]{grove.png}
\caption{Grove GUI}
\label{grovegui}
\end{figure}
The final section of the defmodel pertaining to the generation of three-dimensional graphs has been heavily modified. This model implements the Grove algorithm as described in (insert section reference once this is combined with the full document).  
See Figures \ref{fig:defmodelgrove1}, \ref{fig:defmodelgrove2} for code. 
A sample gui image is located in Figure \ref{grovegui}.
\end{document}
