In probability theory and statistics, the Lévy distribution, named after Paul Lévy, is a continuous probability distribution for a nonnegative random variable. In spectroscopy, this distribution, with frequency as the dependent variable, is known as a van der Waals profile.^{[note 1]} It is a special case of the inversegamma distribution. It is a stable distribution.
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✪ Levy Flight  Part 1

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Transcription
Contents
Definition
The probability density function of the Lévy distribution over the domain is
where is the location parameter and is the scale parameter. The cumulative distribution function is
where is the complementary error function. The shift parameter has the effect of shifting the curve to the right by an amount , and changing the support to the interval [, ). Like all stable distributions, the Levy distribution has a standard form f(x;0,1) which has the following property:
where y is defined as
The characteristic function of the Lévy distribution is given by
Note that the characteristic function can also be written in the same form used for the stable distribution with and :
Assuming , the nth moment of the unshifted Lévy distribution is formally defined by:
which diverges for all n > 0 so that the moments of the Lévy distribution do not exist. The moment generating function is then formally defined by:
which diverges for and is therefore not defined in an interval around zero, so that the moment generating function is not defined per se. Like all stable distributions except the normal distribution, the wing of the probability density function exhibits heavy tail behavior falling off according to a power law:
 as
which shows that Lévy is not just heavytailed but also fattailed. This is illustrated in the diagram below, in which the probability density functions for various values of c and are plotted on a log–log plot.
The standard Lévy distribution satisfies the condition of being stable
 ,
where are independent standard Lévyvariables with .
Related distributions
 If then
 If then (inverse gamma distribution)
Here, the Lévy distribution is a special case of a Pearson type V distribution  If (Normal distribution) then
 If then
 If then (Stable distribution)
 If then (Scaledinversechisquared distribution)
 If then (Folded normal distribution)
Random sample generation
Random samples from the Lévy distribution can be generated using inverse transform sampling. Given a random variate U drawn from the uniform distribution on the unit interval (0, 1], the variate X given by^{[1]}
is Lévydistributed with location and scale . Here is the cumulative distribution function of the standard normal distribution.
Applications
 The frequency of geomagnetic reversals appears to follow a Lévy distribution
 The time of hitting a single point, at distance from the starting point, by the Brownian motion has the Lévy distribution with . (For a Brownian motion with drift, this time may follow an inverse Gaussian distribution, which has the Lévy distribution as a limit.)
 The length of the path followed by a photon in a turbid medium follows the Lévy distribution.^{[2]}
 A Cauchy process can be defined as a Brownian motion subordinated to a process associated with a Lévy distribution.^{[3]}
Footnotes
 ^ "van der Waals profile" appears with lowercase "van" in almost all sources, such as: Statistical mechanics of the liquid surface by Clive Anthony Croxton, 1980, A WileyInterscience publication, ISBN 0471276634, ISBN 9780471276630, [1]; and in Journal of technical physics, Volume 36, by Instytut Podstawowych Problemów Techniki (Polska Akademia Nauk), publisher: Państwowe Wydawn. Naukowe., 1995, [2]
Notes
 ^ How to derive the function for a random sample from a Lévy Distribution: http://www.math.uah.edu/stat/special/Levy.html
 ^ Rogers, Geoffrey L. (2008). "Multiple path analysis of reflectance from turbid media". Journal of the Optical Society of America A. 25 (11): 2879–2883. doi:10.1364/josaa.25.002879.
 ^ Applebaum, D. "Lectures on Lévy processes and Stochastic calculus, Braunschweig; Lecture 2: Lévy processes" (PDF). University of Sheffield. pp. 37–53.
References
 "Information on stable distributions". Retrieved July 13, 2005.  John P. Nolan's introduction to stable distributions, some papers on stable laws, and a free program to compute stable densities, cumulative distribution functions, quantiles, estimate parameters, etc. See especially An introduction to stable distributions, Chapter 1