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\author{黄湘云} % 答辩人
\rel{李再兴} % 导师
\title{空间广义线性混合模型及其在预测流行病中的应用}
\ateneo{硕士论文答辩}
\date{\today}
\keywords{SGLMM}
\subject{硕士论文答辩}

\begin{document}
\titlepageframe

\begin{tframe}

\textbf{Outline}
\begin{enumerate}
  \item Introduction (Motivations and goals)
  \item Literature reviews  
  \item Geostatistical model (SGLMM)
  \item Computing details and simulations
  \item Real data analysis (Applications)
  \item Discussion
\end{enumerate}
\end{tframe}

\section{Intro}

\begin{tframe}
\begin{figure}
\centering
\includegraphics[width=.8\textwidth]{demo01}
\end{figure}
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\begin{figure}
\centering
\includegraphics[width=.8\textwidth]{demo010}
\end{figure}
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\centering
\includegraphics[width=.8\textwidth]{demo011}
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\begin{figure}
\centering
\includegraphics[width=.8\textwidth]{demo03}
\end{figure}
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\section{refs}

\begin{frame}[allowframebreaks]
\frametitle{Frameworks, Packages and Softwares}

\begin{description}
\item[\textbf{R:}] geoR geoRglm spatial PrevMap \\
\citet{R-geoR,R-geoRglm,R-spatial,Giorgi2016}

\item[\textbf{Stan:}] Stan \footnote{\scriptsize \url{http://mc-stan.org/} }  
interfaces with R (RStan) ,Python (PyStan) , MATLAB (MatlabStan) 
and  more \\ \citet{Stan2015,Stan2017}

\item[\textbf{PyMC3:}] Probabilistic programming in Python using PyMC3 \\ \citet{Salvatier2016}

\item[\textbf{JAGS:}] \textbf{J}ust \textbf{A}nother \textbf{G}ibbs \textbf{S}ampler \footnote{\scriptsize \url{https://en.wikipedia.org/wiki/Just_another_Gibbs_sampler}} \\
Bayesian hierarchical models using Markov chain Monte Carlo (MCMC)
\item[\textbf{BUGS:}] \textbf{B}ayesian inference \textbf{U}sing \textbf{G}ibbs \textbf{S}ampling ,
such as winBUGS, OpenBUGS 
\item[\textbf{R-INLA:}] \textbf{I}ntegrated \textbf{N}ested \textbf{L}aplace \textbf{A}pproximations \\
\citet{Rue2009,R-INLA,Rue2017arXiv}
\end{description}


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\bibliography{R-GLMM-pkgs}
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