dissertation_work/Templates/Articles/Article_template.tex

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\documentclass[12pt]{article}
\usepackage{amsmath,
mleftright,
amssymb,
amsthm,
nicefrac,
etoolbox,
xparse,
geometry,
enumitem,
mathtools,
}
\mleftright
\usepackage[colorlinks=true]{hyperref}
\geometry{margin=1in}
\usepackage[sort,capitalize]{cleveref}
\newcommand{\creflastconjunction}{, and\nobreakspace}
\crefformat{equation}{(#2#1#3)}
\crefname{enumi}{item}{items}
\crefname{equation}{}{}
\theoremstyle{plain}
\newtheorem{theorem}{Theorem}[section]
\newtheorem{lemma}[theorem]{Lemma}
\newtheorem{proposition}[theorem]{Proposition}
\newtheorem{corollary}[theorem]{Corollary}
\newtheorem{example}[theorem]{Example}
\newtheorem{setting}[theorem]{Setting}
\newtheorem{conjecture}[theorem]{Conjecture}
\theoremstyle{remark}
\newtheorem{remark}[theorem]{Remark}
\theoremstyle{definition}
\newtheorem{definition}[theorem]{Definition}
\numberwithin{equation}{section}
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\input{commands.tex}
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\begin{document}
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\title{Article template}
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\author{
Joshua Lee Padgett$^{1,2}$
\bigskip
\\
\small{$^1$ Department of Mathematical Sciences, University of Arkansas,}
\vspace{-0.1cm}\\
\small{Arkansas, USA, e-mail: \texttt{padgett@uark.edu}}
\smallskip
\\
\small{$^2$ Center for Astrophysics, Space Physics, and Engineering Research,}
\vspace{-0.1cm}\\
\small{Baylor University, Texas, USA, e-mail: \texttt{padgett@uark.edu}}
}
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\date{\today}
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\maketitle
\begin{abstract}
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Abstract goes here\dots
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\end{abstract}
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\tableofcontents
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\section{Introduction}
\label{sec:intro}
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Add an appropriate introduction\dots
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\section{Monte Carlo approximations}
\label{sec:monte_carlo}
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\begin{athm}{lemma}{Lp_monte_carlo}
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Let
$p \in (2,\infty)$,
$n \in \N$,
let
$ ( \Omega, \cF, \P ) $
be a probability space,
and let
$ X_i \colon \Omega \to \R $, $ i \in \{1, 2, \dots, n\} $,
be i.i.d.\ random variables with
$\E[ \abs{ X_1 } ] < \infty$.
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Then it holds that
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\begin{equation}
\pr[\Big]{ \E \br[\pig]{ \abs[\big]{ \E[X_1] - \tfrac{1}{n} \pr[\big]{ \smallsum_{ i = 1 }^{ n } X_{ i } } }^p } }^{\!\!\nicefrac{1}{p}}
\le
\br[\big]{ \tfrac{p-1}{n} }^{\nicefrac{1}{2}}
\pr[\Big]{ \E \br[\pig]{ \abs[\big]{ X_1 - \E[ X_1 ] }^p } }^{\!\!\nicefrac{1}{p}}
\dpp
\end{equation}
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\end{athm}
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\begin{aproof}
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First, \nobs that
\Enum{
the hypothesis that for all $i\in\{1,2,\allowbreak\dots,\allowbreak n\}$ it holds that
$ X_i\colon \Omega\to \R $
are i.i.d.\ random variables
}
that
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\begin{equation}
\begin{split}
\E\br[\pig]{ \abs[\big]{ \E[X_1] - \tfrac{1}{n} \pr{ \smallsum_{ i = 1 }^{ n } X_{ i } } }^p }
&
=
\E\br[\pig]{ \abs[\big]{ \tfrac{1}{n} \pr{ \smallsum_{ i = 1 }^{ n } (\E[X_1] - X_{ i }) } }^p }
\\
&
=
n^{-p} \, \E\br[\pig]{ \abs[\big]{ \smallsum_{ i = 1 }^{ n } (\E[X_i] - X_{ i }) }^p }
\dpp
\end{split}
\end{equation}
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\Enum{
This
;the fact that for all $i\in\{1,2,\dots,n\}$ it holds that
$ X_i\colon \Omega\to \R $
are i.i.d.\ random variables
;
\eg Rio~\cite[Theorem 2.1]{rio2009moment} (applied with $p \with p$, $(S_i)_{i\in\{0,1,\dots,n\}} \with (\sum_{k=1}^i (\E[X_k] - X_k))_{i\in\{0,1,\dots,n\}}$, $(X_i)_{i \in\{1,2,\dots,n\}} \with (\E[X_i] - X_i)_{i\in\{1,2,\dots,n\}}$ in the notation of Rio~\cite[Theorem 2.1]{rio2009moment})
}
that
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\begin{equation}
\begin{split}
\pr[\Big]{ \E \br[\pig]{ \abs[\big]{ \E[X_1] - \tfrac{1}{n} \pr[\big]{ \smallsum_{ i = 1 }^{ n } X_{ i } } }^p } }^{\!\!\nicefrac{2}{p}}
&
=
\tfrac{1}{n^2} \pr[\Big]{ \E\br[\pig]{ \abs[\big]{ \smallsum_{ i = 1 }^{ n } (\E[X_i] - X_{ i }) }^p } }^{\!\!\nicefrac{2}{p}}
\\
&
\le
\tfrac{(p-1)}{n^2} \br[\Big]{ \smallsum_{ i = 1 }^{ n } \pr[\Big]{ \E\br[\pig]{ \abs[\big]{ \E[X_i] - X_{ i } }^p } }^{\!\!\nicefrac{2}{p}} }
\\
&
=
\tfrac{(p-1)}{n^2} \br[\Big]{ n \pr[\Big]{ \E\br[\pig]{ \abs[\big]{ \E[X_1] - X_{ 1 } }^p } }^{\!\!\nicefrac{2}{p}} }
\\
&
=
\tfrac{(p-1)}{n} \pr[\Big]{ \E\br[\pig]{ \abs[\big]{ \E[X_1] - X_{ 1 } }^p } }^{\!\!\nicefrac{2}{p}}
\dpp
\end{split}
\end{equation}
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\end{aproof}
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\begin{athm}{corollary}{prop:mlp}
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Let $p \in [2,\infty)$,
$n \in \N$,
let
$ ( \Omega, \cF, \P ) $
be a probability space,
and
let
$ X_i \colon \Omega \to \R $,
$ i \in \{1, 2, \dots, n\} $,
be i.i.d.\ random variables with
$\E\br[]{ \abs{ X_1 } } < \infty$.
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Then it holds that
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\begin{equation}\label{eq:2_9}
\pr[\Big]{\E\br[\pig]{ \abs[\big]{ \E[X_1] - \tfrac{1}{n} \pr[]{ {\smallsum_{ i = 1 }^{ n }} X_{ i } } }^p } }^{\!\!\nicefrac{1}{p}}
\le
\br[\big]{ \tfrac{p-1}{n} }^{\nicefrac{1}{2}}
\pr[\Big]{ \E\br[\pig]{ \abs[\big]{ X_1 - \E[ X_1 ] }^p } }^{\!\!\nicefrac{1}{p}}
\dpp
\end{equation}
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\end{athm}
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\begin{aproof}
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\Nobs that
\Enum{
\eg Grohs et al.\ \cite[Lemma 2.3]{grohs2018proof}
;
\cref{Lp_monte_carlo}
}
\cref{eq:2_9}.
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\end{aproof}
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\begin{athm}{definition}{rand_const}
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Let $p \in [2,\infty)$.
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Then we denote by
$\firstConstant{p} \in \R$
the real number given by
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\begin{equation}\label{eq:rand_const}
\firstConstant{p}
=
\inf\left\{ c \in \R \colon \left[
\begin{aligned}
& \text{It holds for every probability space $(\Omega,\cF,\P)$ and every} \\
& \text{random variable $X \colon \Omega \to \R$ with $\E[\abs{X}] < \infty$ that } \\
& \pr[\big]{ \E\br[\big]{ \abs{ X - \E[X] }^p } }^{\!\nicefrac{1}{p}} \le c \pr[\big]{ \E\br[\big]{ \abs{X}^p } }^{\!\nicefrac{1}{p}}
\end{aligned}
\right] \right\}
\dpp
\end{equation}
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\end{athm}
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\begin{athm}{corollary}{cor:exp_bd}
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Let
$p\in[2,\infty)$,
$n\in\N$,
let
$(\Omega,\cF,\P)$
be a probability space,
and let
$X_i \colon \Omega \to \R$, $i\in\{1,2,\dots,n\}$,
be i.i.d.\ random variables with
$\E[\abs{X_1}] < \infty$.
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Then
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\begin{equation}\label{prob_bd1}
\pr[\Big]{\E\br[\pig]{ \abs[\big]{ \E[X_1] - \tfrac{1}{n} \pr[]{ {\smallsum_{ i = 1 }^{ n }} X_{ i } } }^p } }^{\!\!\nicefrac{1}{p}}
\le
\tfrac{\secondConstant{p}}{n^{\nicefrac{1}{2}}} \pr[\Big]{ \E\br[\pig]{ \abs[\big]{ X_1 }^p } }^{\!\!\nicefrac{1}{p}}
\end{equation}
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(cf.\ \cref{rand_const}).
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\end{athm}
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\begin{aproof}
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\Nobs
that
\Enum{
\cref{rand_const}
;
\cref{prop:mlp}
}
that \cref{prob_bd1} holds.
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\end{aproof}
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\bibliographystyle{acm}
\bibliography{bibfile}
\end{document}