The Stress-Strength Model and Its Generalizations: Theory and Applications

By U. Mueller. 2004

57 citations recorded by the source corpus.

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Estimation of δ=P(X<Y) for Burr XII distribution based on the progressively first failure-censored samples (2012, background): “[9] provided an excellent review of the development of the stress–strength up to the year 2003.”
Classical and Bayesian estimation of $$P(X<Y)$$P(X<Y) using upper record values from Kumaraswamy’s distribution (2014, methodology): “A comprehensive account of this topic is presented by Kotz et al. (2003).”
The beta exponentiated Weibull distribution (2013, background): “Hence, R = P(X2 < X1) is a measure of component reliability [24].”
Inference on Reliability in Two-parameter Exponential Stress–strength Model (2007, methodology): “If μ1 = μ2, then the form for R, as shown in (2), is quite complex, and only large sample approach is available (see Kotz et al. 2003, Section 4.2.3). This large sample approach is based on the asymptotic normality of the MLE of R, and its accuracies are yet to be investigated. Small sample conventi”
Inferences on Stress-Strength Reliability from Lindley Distributions (2013, background): “A comprehensive treatment of the different stress-strength models till 2001 can be found in the excellent monograph by Kotz et al. (2003). Some of the recent work on the stress-strength model can be obtained in Kundu and Gupta (2005, 2006), Raqab and Kundu (2005), Kundu and Raqab (2009), Krishnamoor”