Estimating P(Y < X) when X and Y are paired exponential variables

M. M. Shoukri; M. A. Chaudhary; A. Al-Halees

doi:10.1080/00949650410001653142

Estimating P(Y < X) when X and Y are paired exponential variables

M. M. Shoukri, M. A. Chaudhary, A. Al-Halees

Research output: Contribution to journal › Article › peer-review

7 Scopus citations

Abstract

Inference procedures for γ = P(T₂ < T₁) are considered when T₁ and T₂ are correlated and distributed as bivariate exponential. Under this model, asymptotic inference procedures based on maximum likelihood, the method of moments, and generalized estimating equations are developed. Exact confidence limits and the bootstrap BCa confidence on γ are also given. Monte Carlo methods are used to estimate the coverage probabilities with the aim of evaluating the alternative strategies. Two examples are given to illustrate these techniques.

Original language	English (US)
Pages (from-to)	25-38
Number of pages	14
Journal	Journal of Statistical Computation and Simulation
Volume	75
Issue number	1
DOIs	https://doi.org/10.1080/00949650410001653142
State	Published - Jan 2005
Externally published	Yes

Keywords

Bivariate exponential distribution
Bootstrap
Generalized estimating equations
Interval estimation
Maximum likelihood
Simulation

ASJC Scopus subject areas

Statistics and Probability
Modeling and Simulation
Statistics, Probability and Uncertainty
Applied Mathematics

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10.1080/00949650410001653142

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abstract = "Inference procedures for γ = P(T2 < T1) are considered when T1 and T2 are correlated and distributed as bivariate exponential. Under this model, asymptotic inference procedures based on maximum likelihood, the method of moments, and generalized estimating equations are developed. Exact confidence limits and the bootstrap BCa confidence on γ are also given. Monte Carlo methods are used to estimate the coverage probabilities with the aim of evaluating the alternative strategies. Two examples are given to illustrate these techniques.",

keywords = "Bivariate exponential distribution, Bootstrap, Generalized estimating equations, Interval estimation, Maximum likelihood, Simulation",

author = "Shoukri, {M. M.} and Chaudhary, {M. A.} and A. Al-Halees",

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AU - Al-Halees, A.

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N2 - Inference procedures for γ = P(T2 < T1) are considered when T1 and T2 are correlated and distributed as bivariate exponential. Under this model, asymptotic inference procedures based on maximum likelihood, the method of moments, and generalized estimating equations are developed. Exact confidence limits and the bootstrap BCa confidence on γ are also given. Monte Carlo methods are used to estimate the coverage probabilities with the aim of evaluating the alternative strategies. Two examples are given to illustrate these techniques.

AB - Inference procedures for γ = P(T2 < T1) are considered when T1 and T2 are correlated and distributed as bivariate exponential. Under this model, asymptotic inference procedures based on maximum likelihood, the method of moments, and generalized estimating equations are developed. Exact confidence limits and the bootstrap BCa confidence on γ are also given. Monte Carlo methods are used to estimate the coverage probabilities with the aim of evaluating the alternative strategies. Two examples are given to illustrate these techniques.

KW - Bivariate exponential distribution

KW - Bootstrap

KW - Generalized estimating equations

KW - Interval estimation

KW - Maximum likelihood

KW - Simulation

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Estimating P(Y < X) when X and Y are paired exponential variables

Abstract

Keywords

ASJC Scopus subject areas

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