Minimum Variance Unbiased Estimation of P[Y < X] in the Normal Case

DOI10.2307/1268261zbMath0352.62036OpenAlexW4249888595MaRDI QIDQ4122637

Gary D. Kelley, Wayne A. Woodward

Publication date: 1977

Published in: Technometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.2307/1268261

Mathematics Subject Classification ID

Nonparametric estimation (62G05)

Related Items (14)

Estimation of \(R=P(Y<X)\) for three-parameter Weibull distribution ⋮ A note on inference for \(P(X<Y)\) for right truncated exponentially distributed data ⋮ Estimation of pr (a&rsquo;x&gt;&gt;b&rsquo;y) in the mnltiyariate normal case ⋮ Inferences on stress–strength parameter based on GLD5 distribution ⋮ Deconvolution of ℙ(X<Y) with unknown error distributions ⋮ Reliability of stress–strength model for exponentiated Pareto distributions ⋮ Estimation of p{y_p> max(y₁, y₂, …, y_p-1)}in theexponential case ⋮ Inference onP(Y < X)in Bivariate Rayleigh Distribution ⋮ Unnamed Item ⋮ Maximum likelihood estimator of AUC for a bi-exponentiated Weibull model ⋮ Classical and Bayesian estimation ofP(Y<X) for Kumaraswamy's distribution ⋮ Estimation of \(P[Y<X\) for generalized Pareto distribution] ⋮ Some improvements on the Birnbaum-McCarty bound for \(P(Y<X)\) ⋮ Unbiased estimation of \(P(Y<X)\) in the normal case

This page was built for publication: Minimum Variance Unbiased Estimation of P[Y < X] in the Normal Case