AP Statistics Curriculum 2007 Laplace

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Laplace Distribution

Definition: Laplace distribution is a distribution that is symmetrical and more “peaky” than a normal distribution. The dispersion of the data around the mean is higher than that of a normal distribution. Laplace distribution is also sometimes called the double exponential distribution.


Probability density function: For X~Laplace(μ,b), the Laplace probability density function is given by

\frac{1}{2b}exp(-\frac{|x-\mu|}{b})

where

  • e is the natural number (e = 2.71828…)
  • b is a scale parameter (determines the profile of the distribution)
  • μ is the mean
  • x is a random variable


Cumulative density function: The Laplace cumulative distribution function is given by


\left\{\begin{matrix}
\frac{1}{2}\exp(\frac{x-\mu}{b}) & \mbox{if }x < \mu
\\[8pt]
1-\frac{1}{2}\exp(-\frac{x-\mu}{b}) & \mbox{if }x \geq \mu
\end{matrix}\right.

where

  • e is the natural number (e = 2.71828…)
  • b is a scale parameter (determines the profile of the distribution)
  • μ is the mean
  • x is a random variable


Moment generating function: The Laplace moment-generating function is

M(t)=\frac{\exp(\mu t)}{1-b^2 t^2} \mbox{ for }|t|<\frac{1}{b}


Expectation:

E(X)=\mu\!


Variance: The gamma variance is

Var(X)=2b^2\!


Related Distributions



Applications

The Laplace distribution is used for modeling in signal processing, various biological processes, finance, and economics. Examples of events that may be modeled by Laplace distribution include:

  • Credit risk and exotic options in financial engineering
  • Insurance claims
  • Structural changes in switching-regime model and Kalman filter
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