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<record version="4" id="6110">
 <title>empirical distribution function</title>
 <name>EmpiricalDistributionFunction</name>
 <created>2004-08-24 19:34:45</created>
 <modified>2007-12-15 11:00:37</modified>
 <type>Definition</type>
 <creator id="3771" name="CWoo"/>
 <author id="3771" name="CWoo"/>
 <classification>
	<category scheme="msc" code="62G30"/>
 </classification>
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 <content>Let $X_1,\ldots,X_n$ be random variables with realizations $x_i=X_i(\omega)\in\mathbb{R}$, $i=1,\ldots,n$.  The \emph{empirical distribution function} $F_n(x,\omega)$ based on $x_1,\ldots,x_n$ is
$$F_n(x,\omega)=\frac{1}{n}\sum_{i=1}^{n}\chi_{A_i}(x,\omega),$$
where $\chi_{A_i}$ is the indicator function (or characteristic function) and $A_i=\lbrace(x,\omega)\mid x_i\leq x \rbrace$.  Note that each indicator function is itself a random variable.
\par
The empirical function can be alternatively and equivalently defined by using the order statistics $X_{(i)}$ of $X_i$ as:
$$
F_n(x,\omega)= 
\begin{cases}
0 &amp; \text{if $x&lt;x_{(1)}$;}\\
\frac{1}{n} &amp; \text{if $x_{(1)}\leq x&lt;x_{(2)}$, $1\leq k&lt;2$;}\\
\frac{2}{n} &amp; \text{if $x_{(2)}\leq x&lt;x_{(3)}$, $2\leq k&lt;3$;}\\
\vdots\\
\frac{i}{n} &amp; \text{if $x_{(i)}\leq x&lt;x_{(i+1)}$, $i\leq k&lt;i+1$;}\\
\vdots\\
1 &amp; \text{if $x\geq x_{(n)}$;}
\end{cases}
$$
where $x_{(i)}$ is the realization of the random variable $X_{(i)}$ with outcome $\omega$.</content>
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