Estimation of pr[X>Y] for gamma distributions

DOI10.1080/00949658608810967zbMath0609.62129OpenAlexW2060289074MaRDI QIDQ3749993

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Publication date: 1986

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

Full work available at URL: https://doi.org/10.1080/00949658608810967

zbMATH Keywords

simulationmean squared errorexponential distributionsUMVU estimatorML estimatorgamma distributionsuniform minimum variance unbiased estimatortype-II censored samples

Mathematics Subject Classification ID

Nonparametric estimation (62G05) Point estimation (62F10) Reliability and life testing (62N05) Probabilistic methods, stochastic differential equations (65C99)

Related Items (7)

Reliability for lifetime distributions ⋮ Confidence Interval Estimation of P(Y<X) in the Gamma Case ⋮ The simplicity of likelihood based inferences for \(P(X<Y)\) and for the ratio of means in the exponential model ⋮ Estimation ofP(X>Y) with Topp–Leone distribution ⋮ Bootstrapping estimators of P(Y<X) in the gamma case ⋮ Unnamed Item ⋮ Stress-strength reliability estimation under the standard two-sided power distribution

Cites Work

• Unnamed Item
• On the estimation of \(Pr\{ Y<X\}\) for the two-parameter exponential distribution
• Distribution-free confidence bounds for \(P(X < Y)\)
• Estimation of Pr{Y_p> max(Y₁, …, Y_p-1)}: Predictive approach in exponential case
• Estimation of pr{y<x) for truncation parameter distributions
• The estimation ofP(x < Y) for distributions useful in life testing
• A Note on the Estimation of Pr Y < X in the Exponential Case
• On estimating the reliability of a component subject to several different stresses (strengths)
• Nonparametric Upper Confidence Bounds for Pr{Y < X} and Confidence Limits for Pr{Y < X} When X and Y are Normal
• Some Theorems Relevant to Life Testing from an Exponential Distribution

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