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• W3162067151 startingPage "1203" @default.
• W3162067151 abstract "A random variable Y1 is said to be smaller than Y2 in the increasing concave stochastic order if E[ϕ(Y1)]≤E[ϕ(Y2)] for all increasing concave functions ϕ for which the expected values exist, and smaller than Y2 in the increasing convex order if E[ψ(Y1)]≤E[ψ(Y2)] for all increasing convex ψ. This article develops nonparametric estimators for the conditional cumulative distribution functions Fx(y)=ℙ(Y≤y|X=x) of a response variable Y given a covariate X, solely under the assumption that the conditional distributions are increasing in x in the increasing concave or increasing convex order. Uniform consistency and rates of convergence are established both for the K-sample case X∈{1,…,K} and for continuously distributed X." @default.
• W3162067151 created "2021-05-24" @default.
• W3162067151 creator A5015268540 @default.
• W3162067151 date "2022-10-03" @default.
• W3162067151 modified "2023-10-16" @default.
• W3162067151 title "Consistent Estimation of Distribution Functions under Increasing Concave and Convex Stochastic Ordering" @default.
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• W3162067151 doi "https://doi.org/10.1080/07350015.2022.2116026" @default.
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