The Advanced Theory of Statistics, Vol. 1: Distribution Theory

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Adaptivity and Computation-Statistics Tradeoffs for Kernel and Distance based High Dimensional Two Sample Testing (2015, neutral): “The expectations follow directly from the results of Magnus [1979] and Kendall and Stuart [1977].”
Distributional Transformations, Orthogonal Polynomials, and Stein Characterizations (2005, methodology): “existence of the family of Gegenbauer transformations. This family of distribution is a special case of the centered Pearson Type I-distributions, sometimes also called Beta Type I-distributions, see [23], p.150. We note that for λ = 1/2 we obtain the uniform distribution U[−1,1], for λ = 0 the arcs”
Continuous latent variable models for dimensionality reduction and sequential data reconstruction (2001, methodology): “Cumulant-based approximations to the differential entropy arise from a Gram-Charlier or Edgeworth polynomial expansion of the density (Kendall and Stuart, 1977) and have been also used in the context of independent component analysis (Comon, 1994).”
A note on the applicability of log-Gumbel and log-logistic probability distributions in hydrological analyses: I. Known pdf (2002, background): “It is worth mentioning that even the popular lognormal distribution is not uniquely determined by its existing moments (Kendall & Stuart, 1969).”