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<record version="3" id="5981">
 <title>survivor function</title>
 <name>SurvivorFunction</name>
 <created>2004-07-02 18:21:28</created>
 <modified>2007-12-18 11:09:39</modified>
 <type>Definition</type>
 <creator id="3771" name="CWoo"/>
 <author id="3771" name="CWoo"/>
 <classification>
	<category scheme="msc" code="62N99"/>
	<category scheme="msc" code="62P05"/>
 </classification>
 <defines>
	<concept>survival time</concept>
 </defines>
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 <content>Let $Y$ be a random variable with cumulative probability distribution function $F_Y(y)$.  Then the \emph{survivor function} $S(y)$ is defined to be:
$$S(y) = 1 - F_Y(y) = P(Y\geq y).$$
The random variable $Y$ is often called the \emph{survival time}.

The survivor function is the probability of survival beyond time $Y=y$.

\textbf{Examples.} The three most commonly used distribution functions for survival time are:
\begin{enumerate}
\item \PMlinkname{exponential distribution}{ExponentialRandomVariable}, with $S(y)=\exp(-\gamma y).$
\item Weibull distribution, with $S(y)=\exp(-y^{\gamma})$ using the standard Weibull distribution.
\item extreme-value distribution, with $S(y)=\exp(-\exp(\displaystyle{\frac{y-\alpha}{\beta}})).$
\end{enumerate}</content>
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