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Tukey lambda distribution

Formalized by John Tukey, the Tukey lambda distribution is a continuous, symmetric probability distribution defined in terms of its quantile function. It is typically used to identify an appropriate distribution (see the comments below) and not used in statistical models directly.

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CDF
( Q ( p ; λ ) , p ) f o r a n y p : 0 ≤ p ≤ 1 {\displaystyle {\Bigl (}\ Q(p;\lambda ),\ p\ {\Bigr )}~~{\mathsf {for\ any}}~~p\;:\;0\leq \ p\ \leq \ 1~} (general case) 1 e − x +…
CF
ϕ ( t ; λ ) = ∫ 0 1 exp ⁡ ( i t Q ( p ; λ ) ) d ⁡ p {\displaystyle \phi (t;\lambda )=\int _{0}^{1}\exp {\bigl (}\ i\ t\ Q(p;\lambda )\ {\bigr )}\ \operatorname {d} p~}
Entropy
h ( λ ) = ∫ 0 1 ln ⁡ ( q ( p ; λ ) ) d ⁡ p {\displaystyle h(\lambda )=\int _{0}^{1}\ln {\bigl (}\ q(p;\lambda )\ {\bigr )}\ \operatorname {d} p~}
Excess kurtosis
( 2 λ + 1 ) 2 ⋅ g 2 2 ⋅ ( 3 g 2 2 − 4 g 1 g 3 + g 4 ) ( 8 λ + 2 ) ⋅ g 4 ⋅ ( g 1 2 − g 2 ) 2 − 3 i f λ > 0 , {\displaystyle ~{\frac {\ (2\ \lambda +1)^{2}\cdot g_{2}^{2}\cdot {\b…
Mean
0 i f λ > − 1 {\displaystyle 0\quad ~{\mathsf {if}}~\quad \lambda >-1\ }
Median
0

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Overview

Quantile function

Moments

L-moments

Comments

Generalization

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Map overview Semantic statistics

Tukey lambda distribution

Nodes29
Edges28
Triples30
Avg. degree1.93
Density0.068966
Components1

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Tukey lambda distribution

Top relations

related to Comments · 7
Tukey lambda distribution → Based, For, PPCC, The, The Tukey, Tukey, Values
related to Quantile function · 5
Tukey lambda distribution → CDF, For, PDF, The Tukey, Tukey
related to Moments · 3
Tukey lambda distribution → More, The, The Tukey
is a · 2
Tukey lambda distribution → continuous, symmetric distribution
CDF · 1
Tukey lambda distribution → ( Q ( p ; λ ) , p ) f o r a n y p : 0 ≤ p ≤ 1 {\displaystyle {\Bigl (}\ Q(p;\lambda ),\ p\ {\Bigr )}~~{\mathsf {for\ any}}~~p\;:\;0\leq \ p\ \leq \ 1~} (general case) 1 e − x +…
CF · 1
Tukey lambda distribution → ϕ ( t ; λ ) = ∫ 0 1 exp ⁡ ( i t Q ( p ; λ ) ) d ⁡ p {\displaystyle \phi (t;\lambda )=\int _{0}^{1}\exp {\bigl (}\ i\ t\ Q(p;\lambda )\ {\bigr )}\ \operatorname {d} p~}
Entropy · 1
Tukey lambda distribution → h ( λ ) = ∫ 0 1 ln ⁡ ( q ( p ; λ ) ) d ⁡ p {\displaystyle h(\lambda )=\int _{0}^{1}\ln {\bigl (}\ q(p;\lambda )\ {\bigr )}\ \operatorname {d} p~}
Excess kurtosis · 1
Tukey lambda distribution → ( 2 λ + 1 ) 2 ⋅ g 2 2 ⋅ ( 3 g 2 2 − 4 g 1 g 3 + g 4 ) ( 8 λ + 2 ) ⋅ g 4 ⋅ ( g 1 2 − g 2 ) 2 − 3 i f λ 0 , {\displaystyle ~{\frac {\ (2\ \lambda +1)^{2}\cdot g_{2}^{2}\cdot {\b…
Mean · 1
Tukey lambda distribution → 0 i f λ − 1 {\displaystyle 0\quad ~{\mathsf {if}}~\quad \lambda -1\ }
Median · 1
Tukey lambda distribution → 0

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Important terminology

distribution lambda tukey function probability quantile parameter distributions form pdf shape symmetric value density displaystyle l-moments values data given terms

Entity relationships Subject–Predicate–Object triples

SubjectPredicateObjectConfidenceSrc
Tukey lambda distributionCDF( Q ( p ; λ ) , p ) f o r a n y p : 0 ≤ p ≤ 1 {\displaystyle {\Bigl (}\ Q(p;\lambda ),\ p\ {\Bigr )}~~{\mathsf {for\ any}}~~p\;:\;0\leq \ p\ \leq \ 1~} (general case) 1 e − x +…1.00infobox
Tukey lambda distributionCFϕ ( t ; λ ) = ∫ 0 1 exp ⁡ ( i t Q ( p ; λ ) ) d ⁡ p {\displaystyle \phi (t;\lambda )=\int _{0}^{1}\exp {\bigl (}\ i\ t\ Q(p;\lambda )\ {\bigr )}\ \operatorname {d} p~}1.00infobox
Tukey lambda distributionEntropyh ( λ ) = ∫ 0 1 ln ⁡ ( q ( p ; λ ) ) d ⁡ p {\displaystyle h(\lambda )=\int _{0}^{1}\ln {\bigl (}\ q(p;\lambda )\ {\bigr )}\ \operatorname {d} p~}1.00infobox
Tukey lambda distributionExcess kurtosis( 2 λ + 1 ) 2 ⋅ g 2 2 ⋅ ( 3 g 2 2 − 4 g 1 g 3 + g 4 ) ( 8 λ + 2 ) ⋅ g 4 ⋅ ( g 1 2 − g 2 ) 2 − 3 i f λ > 0 , {\displaystyle ~{\frac {\ (2\ \lambda +1)^{2}\cdot g_{2}^{2}\cdot {\b…1.00infobox
Tukey lambda distributionMean0 i f λ > − 1 {\displaystyle 0\quad ~{\mathsf {if}}~\quad \lambda >-1\ }1.00infobox
Tukey lambda distributionMedian01.00infobox
Tukey lambda distributionMode01.00infobox
Tukey lambda distributionNotationTukey(λ)1.00infobox
Tukey lambda distributionParametersλ ∈ ℝ — shape parameter1.00infobox
Tukey lambda distributionPDF( Q ( p ; λ ) , 1 q ( p ; λ ) ) f o r a n y p : 0 ≤ p ≤ 1 {\displaystyle \left(\ Q(\ p\ ;\lambda \ ),\ {\frac {1}{\ q(\ p\ ;\lambda \ )\ }}\ \right)\quad ~{\mathsf {for\ any}}~\…1.00infobox
Tukey lambda distributionSkewness0 i f λ > − 1 3 {\displaystyle 0\qquad \qquad ~{\mathsf {if}}~\quad \lambda >-{\tfrac {\ 1\ }{3}}\ }1.00infobox
Tukey lambda distributionSupportx ∈ [ −.mw-parser-output .sfrac{white-space:nowrap}.mw-parser-output .sfrac.tion,.mw-parser-output .sfrac .tion{display:inline-block;vertical-align:-0.5em;font-size:85%;text-ali…1.00infobox
Tukey lambda distributionVariance2 λ 2 ( 1 1 + 2 λ − Γ ( λ + 1 ) 2 Γ ( 2 λ + 2 ) ) i f λ > − 1 2 {\displaystyle {\frac {2}{\ \lambda ^{2}\ }}\left(\ {\frac {1}{\ 1+2\ \lambda \ }}-{\frac {\ \Gamma \,\!(\lambda…1.00infobox
Tukey lambda distributionis acontinuous0.90text
Tukey lambda distributionis asymmetric distribution0.90text

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