Let $ X $ and $ Y $ follow independent exponential-Rayleigh distributions when the shape and scale parameters are different. In this paper, the maximum likelihood and the Bayes estimates of the stress-strength parameter $ \delta = P(X < Y) $ are derived. Based on the sampling technique, we use the asymptotic distribution and the Bayes estimate of $ \delta $ to construct the corresponding confidence and credible intervals. Analyses of two data sets, one simulated data and the other real-life data, are given for illustrative purposes. Finally, Monte Carlo simulations are used to compare the different methods discussed here.
Citation: Mohammed S. Kotb, Ghaithah A. Alzhrani. Inference of $ P\left(X < Y\right) $ for two-parameter exponential-Rayleigh distribution with applications[J]. AIMS Mathematics, 2025, 10(7): 16526-16550. doi: 10.3934/math.2025740
Let $ X $ and $ Y $ follow independent exponential-Rayleigh distributions when the shape and scale parameters are different. In this paper, the maximum likelihood and the Bayes estimates of the stress-strength parameter $ \delta = P(X < Y) $ are derived. Based on the sampling technique, we use the asymptotic distribution and the Bayes estimate of $ \delta $ to construct the corresponding confidence and credible intervals. Analyses of two data sets, one simulated data and the other real-life data, are given for illustrative purposes. Finally, Monte Carlo simulations are used to compare the different methods discussed here.
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Mohammed S. Kotb, Ghaithah A. Alzhrani. Inference of $ P\left(X < Y\right) $ for two-parameter exponential-Rayleigh distribution with applications[J]. AIMS Mathematics, 2025, 10(7): 16526-16550. doi: 10.3934/math.2025740
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