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 <title>Weibull random variable</title>
 <name>WeibullRandomVariable</name>
 <created>2004-06-24 19:55:04</created>
 <modified>2007-06-06 11:40:44</modified>
 <type>Definition</type>
 <creator id="3771" name="CWoo"/>
 <author id="3771" name="CWoo"/>
 <classification>
	<category scheme="msc" code="60E05"/>
	<category scheme="msc" code="62E15"/>
	<category scheme="msc" code="62N99"/>
	<category scheme="msc" code="62P05"/>
 </classification>
 <synonyms>
	<synonym concept="Weibull random variable" alias="Weibull distribution"/>
	<synonym concept="Weibull random variable" alias="Rayleigh distribution"/>
 </synonyms>
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 <content>$X$ is a \emph{Weibull random variable} if it has a probability density function, given by
$$f_X(x)=\frac{\gamma}{\alpha}(\frac{x-\mu}{\alpha})^{\gamma-1}
e^{-(\frac{x-\mu}{\alpha})^\gamma}$$
where $\alpha,\gamma,\mu\in\mathbb{R}$, $\alpha,\gamma&gt;0$ and $x\ge\mu$.  $\alpha$ is the \emph{scale parameter}, $\gamma$ is the \emph{shape parameter}, and $\mu$ is the \emph{location parameter}.

Notation for $X$ having a Weibull distribution is $X\sim \mbox{Wei}(\alpha,\gamma,\mu)$.  Usually, the location and scale parameters are dropped by the transformation $$Y=\frac{X-\mu}{\alpha}$$ so that $Y\sim \mbox{Wei}(\gamma):=\mbox{Wei}(1,\gamma,0)$.  The resulting distribution is called the \emph{standard Weibull}, or \emph{Rayleigh distribution}:
$$f_X(x)=\gamma x^{\gamma-1}\operatorname{exp}(-x^\gamma)$$

\textbf{\PMlinkescapetext{Properties}}:
Given a standard Weibull distribution $X\sim \mbox{Wei}(\gamma)$:
\begin{enumerate}
\item 
$\operatorname{E}[X]=\Gamma(\frac{\gamma+1}{\gamma})$, where $\Gamma$ is the gamma function
\item 
Median = $(\operatorname{ln}2)^{\frac{1}{\gamma}}$
\item
Mode $= \begin{cases}
(1-\frac{1}{\gamma})^{1/\gamma} &amp; \mbox{if $\gamma&gt;1$}\\
0 &amp; \mbox{otherwise} \end{cases}$
\item 
$\operatorname{Var}[X]=\Gamma(\frac{\gamma+2}{\gamma})-\Gamma(\frac{\gamma+1}{\gamma})^2$
\item 
$X\sim \mbox{Wei}(\alpha,\gamma,0)$ iff $X^{\gamma}\sim \mbox{Exp}(\alpha^\gamma)$, the exponential distribution with parameter $\alpha^\gamma$
\end{enumerate}

\textbf{Remark.}
The Weibull distribution is often used to model reliability or lifetime of \PMlinkescapetext{products} such as light bulbs.</content>
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