TY - JOUR
T1 - On An Intriguing Distributional Identity
AU - Jones, M. C.
AU - Marchand, Éric
AU - Strawderman, William E.
N1 - Funding Information:
We are indebted to a referee and an associate editor for useful suggestions and constructive comments. We are grateful to Aziz L’Moudden for numerical evaluations leading to the Gamma application. Otherwise, we are thankful to Tomasz Kaczynski for a useful discussion of some technical aspects of Theorem 2.1. Eric Marchand’s and William Strawderman’s research are partially supported by the Natural Sciences and Engineering Research Council of Canada and grants from the Simons Foundation (#209035 and #418098), respectively.
Publisher Copyright:
© 2018, © 2018 American Statistical Association.
PY - 2019/1/2
Y1 - 2019/1/2
N2 - For a continuous random variable X with support equal to (a, b), with c.d.f. F, and g: Ω 1 → Ω 2 a continuous, strictly increasing function, such that Ω 1 ∩Ω 2 ⊇(a, b), but otherwise arbitrary, we establish that the random variables F(X) − F(g(X)) and F(g − 1 (X)) − F(X) have the same distribution. Further developments, accompanied by illustrations and observations, address as well the equidistribution identity U − ψ(U) = d ψ − 1 (U) − U for U ∼ U(0, 1), where ψ is a continuous, strictly increasing and onto function, but otherwise arbitrary. Finally, we expand on applications with connections to variance reduction techniques, the discrepancy between distributions, and a risk identity in predictive density estimation.
AB - For a continuous random variable X with support equal to (a, b), with c.d.f. F, and g: Ω 1 → Ω 2 a continuous, strictly increasing function, such that Ω 1 ∩Ω 2 ⊇(a, b), but otherwise arbitrary, we establish that the random variables F(X) − F(g(X)) and F(g − 1 (X)) − F(X) have the same distribution. Further developments, accompanied by illustrations and observations, address as well the equidistribution identity U − ψ(U) = d ψ − 1 (U) − U for U ∼ U(0, 1), where ψ is a continuous, strictly increasing and onto function, but otherwise arbitrary. Finally, we expand on applications with connections to variance reduction techniques, the discrepancy between distributions, and a risk identity in predictive density estimation.
KW - Equidistribution
KW - Identity
KW - Uniform distribution
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U2 - 10.1080/00031305.2017.1375984
DO - 10.1080/00031305.2017.1375984
M3 - Article
AN - SCOPUS:85047985853
SN - 0003-1305
VL - 73
SP - 16
EP - 21
JO - American Statistician
JF - American Statistician
IS - 1
ER -