EstimatingP(Y < X) whenXandYare paired exponential variables

DOI10.1080/00949650410001653142zbMath1059.62020OpenAlexW2126238977WikidataQ57635298 ScholiaQ57635298MaRDI QIDQ4663379

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Publication date: 30 March 2005

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949650410001653142

zbMATH Keywords

bootstrapsimulationmaximum likelihoodinterval estimationgeneralized estimating equationsbivariate exponential distribution

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Point estimation (62F10) Bootstrap, jackknife and other resampling methods (62F40) Monte Carlo methods (65C05) Estimation in survival analysis and censored data (62N02)

Related Items (4)

Posterior propriety of bivariate lomax distribution under objective priors ⋮ Objective Bayesian inference for the reliability in a bivariate Lomax distribution ⋮ Data transformation for confidence interval improvement: an application to the estimation of stress-strength model reliability ⋮ Classical and Bayesian estimation ofP(Y<X) for Kumaraswamy's distribution

Cites Work

• Unnamed Item
• Longitudinal data analysis using generalized linear models
• A comparison of three point estimators for \(P(Y<X)\) in the normal case
• Multivariate Generalizations of the Proportional Hazards Model
• Paired Observations from a Survival Distribution
• A Concordance Test for Independence in the Presence of Censoring
• A model for association in bivariate life tables and its application in epidemiological studies of familial tendency in chronic disease incidence
• Nonparametric Upper Confidence Bounds for Pr{Y < X} and Confidence Limits for Pr{Y < X} When X and Y are Normal
• The Estimation of Pr (Y < X) in the Normal Case
• Inference for reliability and stress-strength for a scaled Burr type \(X\) distribution

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