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drw_results_ch_jav.tex
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drw_results_ch_jav.tex
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\documentclass[11pt]{article}
\usepackage[left=40pt,right=40pt,top=30pt,bottom=30pt]{geometry}
\usepackage{natbib} % See geometry.pdf to learn the
%[left=20pt,right=20pt,top=20pt,bottom=15pt]layout options. There are lots.
\geometry{letterpaper} % ... or a4paper or a5paper or ...
%\geometry{landscape} % Activate for for rotated page geometry
%\usepackage[parfill]{parskip} % Activate to begin paragraphs with an empty line rather than an indent
\usepackage{graphicx}
% for matrix2latex output
\providecommand{\e}[1]{\ensuremath{\times 10^{#1}}}
\usepackage{amsmath}
\usepackage{booktabs}
\usepackage{caption}
\usepackage{amssymb}
\usepackage{epstopdf}
\title{DRW analysis }\begin{document}\maketitle\section{Chelsea results}\begin{table}[htp]
\begin{center}
\caption{Chelsea results, $x_{0}$ is the true value, rms = $(\log(x_{fit,75\%}) - \log(x_{fit,25\%} ) 0.7413$ }
\begin{tabular}{cccccccccc}
\toprule
{} & \multicolumn{3}{c}{Short} & \multicolumn{3}{c}{Medium} & \multicolumn{3}{c}{Long}\\\cmidrule(r){2-4}\cmidrule(r){5-7}\cmidrule(r){8-10}
{} & {err1} & {err2} & {err3} & {err1} & {err2} & {err3} & {err1} & {err2} & {err3}\\
\midrule
$\log(\tau_{fit})_{med}- \log(\tau_{0})$ & $-0.196$ & $-0.205$ & $-0.214$ & $-0.073$ & $-0.074$ & $-0.079$ & $-0.020$ & $-0.019$ & $-0.020$\\
$\log(\tau_{fit})_{rms}$ & $0.311$ & $0.342$ & $0.407$ & $0.195$ & $0.219$ & $0.267$ & $0.104$ & $0.120$ & $0.134$\\
$\log(\sigma_{fit})_{med} -\log(\sigma_{0})$ & $-0.097$ & $-0.097$ & $-0.093$ & $-0.035$ & $-0.035$ & $-0.037$ & $-0.007$ & $-0.008$ & $-0.008$\\
$\log(\sigma_{fit})_{rms}$ & $0.157$ & $0.160$ & $0.176$ & $0.100$ & $0.102$ & $0.106$ & $0.051$ & $0.053$ & $0.054$\\
$\log(\hat{\sigma}_{fit})_{med} -\log(\hat{\sigma}_{0})$ & $0.003$ & $0.012$ & $0.023$ & $0.004$ & $0.004$ & $0.007$ & $0.004$ & $0.001$ & $0.003$\\
$\log(\hat{\sigma}_{fit})_{rms}$ & $0.018$ & $0.064$ & $0.106$ & $0.011$ & $0.041$ & $0.057$ & $0.009$ & $0.027$ & $0.047$\\
$\log(K_{fit})_{med} -\log(K_{0})$ & $-0.244$ & $-0.269$ & $-0.263$ & $-0.091$ & $-0.091$ & $-0.106$ & $-0.022$ & $-0.024$ & $-0.024$\\
$\log(K_{fit})_{rms}$ & $0.391$ & $0.415$ & $0.488$ & $0.245$ & $0.258$ & $0.312$ & $0.129$ & $0.145$ & $0.156$\\
\bottomrule
\end{tabular}
\end{center}
\end{table}
\section{Javelin results}\begin{table}[htp]
\begin{center}
\caption{Javelin results}
\begin{tabular}{ccccccccccc}
\toprule
{ } & \multicolumn{6}{c}{Short} & \multicolumn{4}{c}{Medium}\\\cmidrule(r){2-7}\cmidrule(r){8-11}
{ } & \multicolumn{3}{c}{no,} & \multicolumn{3}{c}{yes,} & \multicolumn{2}{c}{no,} & \multicolumn{2}{c}{yes,}\\\cmidrule(r){2-4}\cmidrule(r){5-7}\cmidrule(r){8-9}\cmidrule(r){10-11}
{ } & {err1} & {err2} & {err3} & {err1} & {err2} & {err3} & {err1} & {err2} & {err1} & {err2}\\
\midrule
$\log(\tau_{fit})_{med}- \log(\tau_{0})$ & $0.522$ & $0.792$ & $1.061$ & $-0.314$ & $-0.339$ & $-0.391$ & $0.166$ & $0.227$ & $-0.119$ & $-0.125$\\
$\log(\tau_{fit})_{rms}$ & $0.612$ & $0.689$ & $0.678$ & $0.221$ & $0.247$ & $0.284$ & $0.391$ & $0.489$ & $0.172$ & $0.188$\\
$\log(\sigma_{fit})_{med} -\log(\sigma_{0})$ & $0.260$ & $0.369$ & $0.481$ & $-0.156$ & $-0.153$ & $-0.153$ & $0.083$ & $0.111$ & $-0.059$ & $-0.057$\\
$\log(\sigma_{fit})_{rms}$ & $0.307$ & $0.331$ & $0.318$ & $0.111$ & $0.115$ & $0.115$ & $0.194$ & $0.229$ & $0.085$ & $0.086$\\
$\log(\hat{\sigma}_{fit})_{med} -\log(\hat{\sigma}_{0})$ & $-1.281$ & $-1.290$ & $-1.307$ & $-1.278$ & $-1.256$ & $-1.225$ & $-1.279$ & $-1.286$ & $-1.279$ & $-1.273$\\
$\log(\hat{\sigma}_{fit})_{rms}$ & $0.017$ & $0.065$ & $0.112$ & $0.016$ & $0.061$ & $0.100$ & $0.010$ & $0.041$ & $0.010$ & $0.040$\\
$\log(K_{fit})_{med} -\log(K_{0})$ & $0.013$ & $0.332$ & $0.666$ & $-1.032$ & $-1.060$ & $-1.108$ & $-0.433$ & $-0.350$ & $-0.788$ & $-0.794$\\
$\log(K_{fit})_{rms}$ & $0.764$ & $0.853$ & $0.832$ & $0.274$ & $0.286$ & $0.339$ & $0.491$ & $0.608$ & $0.213$ & $0.222$\\
\bottomrule
\end{tabular}
\end{center}
\end{table}
\end{document}