\documentclass[12pt]{article} \usepackage{ amssymb, amsmath, bm, graphicx } \addtolength{\textheight}{1.6in} \addtolength{\topmargin}{-0.75in} \addtolength{\textwidth}{1.6in} \addtolength{\evensidemargin}{-0.8in} \addtolength{\oddsidemargin}{-0.9in} \setlength{\parskip}{0.1in} \setlength{\parindent}{0.0in} \raggedbottom \newcommand{\given}{\, | \,} \begin{document} \begin{flushleft} University of California, Santa Cruz \\ Department of Applied Mathematics and Statistics \\ Baskin School of Engineering \end{flushleft} \Large \begin{center} AMS 206 (\textsf{Applied Bayesian Statistics}) \textbf{Incorporating .pdf Plots Into \texttt{LaTeX}} \end{center} \normalsize In an \texttt{R} tutorial on the course web page, I showed you how to use the \texttt{pdf} function in \texttt{R} to spool a plot into a \texttt{.pdf} file; here's an example of how to incorporate such plots into a \texttt{LaTeX} document. Table \ref{t:r-code} presents the \texttt{R} code used to make the plot presented below and illustrates the use of the \texttt{table} environment in \texttt{LaTeX}. Let's suppose that you have a directory called \texttt{AMS-206} in which you keep all of your files for this course. \begin{table}[h!] \centering \caption{\textit{\texttt{R} code to create the plot incorporated into this document.}} \begin{quote} \begin{verbatim} # code to illustrate various aspects of plotting functions in R # # here you would use a setwd command (or the `Change dir...' option # from the File pull-down menu in R) to ensure that the .pdf file # is stored in your directory AMS-206 # p <- seq( 0.001, 0.999, length = 500 ) plot( p, log( p / ( 1 - p ) ), type = 'l', lwd = 2, ylab = 'logit( p ) = log( p / ( 1 - p ) )' ) text( 0.4, 4.0, 'this is the logistic or logit transformation;' ) text( 0.4, 3.25, 'it maps probabilities onto the whole real line' ) lines( p, 4 * p - 2, lty = 2, lwd = 2, col = 'red' ) text( 0.6, -4.0, "it's approximately linear for p in ( 0.3, 0.7 )" ) # # use this code to make a PDF file to incorporate into your Latex document # pdf( 'ams-206-logit-plot.pdf' ) plot( p, log( p / ( 1 - p ) ), type = 'l', lwd = 2, ylab = 'logit( p ) = log( p / ( 1 - p ) )' ) text( 0.4, 4.0, 'this is the logistic or logit transformation;' ) text( 0.4, 3.25, 'it maps probabilities onto the whole real line' ) lines( p, 4 * p - 2, lty = 2, col = 'red' ) text( 0.6, -4.0, "it's approximately linear for p in ( 0.3, 0.7 )" ) dev.off( ) \end{verbatim} \end{quote} \label{t:r-code} \end{table} Figure \ref{f:logit-transformation} displays the \texttt{.pdf} graph created with the \texttt{R} code in Table \ref{t:r-code}. To use the \texttt{includegraphics} command in \texttt{LaTeX}, you'll need to include the \texttt{graphicx} package in the \texttt{usepackage} specification in the preamble of your \texttt{LaTeX} document (the second line of \texttt{LaTeX} code in this document). \begin{figure}[t!] \centering \caption{\textit{A plot of logit$( p )$ against $p$, to examine its nonlinearity.}} \vspace*{-0.1in} \includegraphics[ scale = 0.7 ]{ams-206-logit-plot.pdf} \vspace*{-0.1in} \label{f:logit-transformation} \end{figure} \begin{table}[t!] \centering \caption{\textit{\texttt{Maple} code to work out the Taylor expansion of logit$( p )$ around $p = 0.5$ to third order.}} \begin{quote} \begin{verbatim} help( taylor ); taylor( log( p / ( 1 - p ) ), p = 0.5, 3 ); 4.000000000 ( p - 0.5 ) + O[ ( p - 0.5 )^3 ] \end{verbatim} \end{quote} \label{t:maple-code} \end{table} Table \ref{t:maple-code} gives \texttt{Maple} code that computes the linear Taylor expansion used to plot the dotted line in Figure \ref{f:logit-transformation}. You can see that there is no quadratic term in this expansion; this explains why the linear approximation is so good over such a wide range of values of $p$. \end{document}