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Lévy distribution

In probability theory and statistics, the Lévy distribution, named after Paul Lévy, is a continuous probability distribution for a non-negative random variable. In spectroscopy, this distribution, with frequency as the dependent variable, is known as a van der Waals profile. It is a special case of the inverse-gamma distribution and a stable distribution.

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CDF
erfc ( c 2 ( x − μ ) ) {\displaystyle {\textrm {erfc}}\left({\sqrt {\frac {c}{2(x-\mu )}}}\right)}
CF
e i μ t − − 2 i c t {\displaystyle e^{i\mu t-{\sqrt {-2ict}}}}
Entropy
1 + 3 γ + ln ⁡ ( 16 π c 2 ) 2 {\displaystyle {\frac {1+3\gamma +\ln(16\pi c^{2})}{2}}} where γ {\displaystyle \gamma } is the Euler-Mascheroni constant
Excess kurtosis
undefined
Mean
∞ {\displaystyle \infty }
Median
μ + c / 2 ( erfc − 1 ( 1 / 2 ) ) 2 {\displaystyle \mu +c/2({\textrm {erfc}}^{-1}(1/2))^{2}\,}

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Overview

Definition

Related distributions

Random-sample generation

Applications

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Map overview Semantic statistics

Lévy distribution

Nodes38
Edges37
Triples42
Avg. degree1.95
Density0.052632
Components1

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Lévy distribution

Top relations

related to Related distributions · 10
Lévy distribution → FoldedNormal, Here, If, Inv-Gamma, Levy, Lévy, Normal, Pearson, Scale-inv, Stable
has application · 6
Lévy distribution → Brownian, Cauchy, For, Gaussian, Lévy, The
related to Random-sample generation · 6
Lévy distribution → Given, Here, Lévy, Lévy-distributed, Phi, Random
related to External links · 3
Lévy distribution → Eric, MathWorld, Weisstein
related to Definition · 2
Lévy distribution → Lévy, The
CDF · 1
Lévy distribution → erfc ( c 2 ( x − μ ) ) {\displaystyle {\textrm {erfc}}\left({\sqrt {\frac {c}{2(x-\mu )}}}\right)}
CF · 1
Lévy distribution → e i μ t − − 2 i c t {\displaystyle e^{i\mu t-{\sqrt {-2ict}}}}
Entropy · 1
Lévy distribution → 1 + 3 γ + ln ⁡ ( 16 π c 2 ) 2 {\displaystyle {\frac {1+3\gamma +\ln(16\pi c^{2})}{2}}} where γ {\displaystyle \gamma } is the Euler-Mascheroni constant
Excess kurtosis · 1
Lévy distribution → undefined
Mean · 1
Lévy distribution → ∞ {\displaystyle \infty }

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Important terminology

distribution displaystyle mu lévy stable operatorname sim function sqrt levy frac distributions probability normal infty pi x- density cumulative standard

Entity relationships Subject–Predicate–Object triples

SubjectPredicateObjectConfidenceSrc
Lévy distributionCDFerfc ( c 2 ( x − μ ) ) {\displaystyle {\textrm {erfc}}\left({\sqrt {\frac {c}{2(x-\mu )}}}\right)}1.00infobox
Lévy distributionCFe i μ t − − 2 i c t {\displaystyle e^{i\mu t-{\sqrt {-2ict}}}}1.00infobox
Lévy distributionEntropy1 + 3 γ + ln ⁡ ( 16 π c 2 ) 2 {\displaystyle {\frac {1+3\gamma +\ln(16\pi c^{2})}{2}}} where γ {\displaystyle \gamma } is the Euler-Mascheroni constant1.00infobox
Lévy distributionExcess kurtosisundefined1.00infobox
Lévy distributionMean∞ {\displaystyle \infty }1.00infobox
Lévy distributionMedianμ + c / 2 ( erfc − 1 ( 1 / 2 ) ) 2 {\displaystyle \mu +c/2({\textrm {erfc}}^{-1}(1/2))^{2}\,}1.00infobox
Lévy distributionMGFundefined1.00infobox
Lévy distributionModeμ + c 3 {\displaystyle \mu +{\frac {c}{3}}}1.00infobox
Lévy distributionParametersμ {\displaystyle \mu } location; c > 0 {\displaystyle c>0\,} scale1.00infobox
Lévy distributionPDFc 2 π e − c 2 ( x − μ ) ( x − μ ) 3 / 2 {\displaystyle {\sqrt {\frac {c}{2\pi }}}~~{\frac {e^{-{\frac {c}{2(x-\mu )}}}}{(x-\mu )^{3/2}}}}1.00infobox
Lévy distributionQuantileμ + σ 2 ( erfc − 1 ( p ) ) 2 {\displaystyle \mu +{\frac {\sigma }{2\left({\textrm {erfc}}^{-1}(p)\right)^{2}}}}1.00infobox
Lévy distributionSkewnessundefined1.00infobox
Lévy distributionSupportx ∈ ( μ , ∞ ) {\displaystyle x\in (\mu ,\infty )}1.00infobox
Lévy distributionVariance∞ {\displaystyle \infty }1.00infobox
Lévy distributionis aspecial case of a Pearson type V distribution.If Y0.90text

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