Joint Bivariate Exponential Distribution

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SUMMARY

The discussion focuses on the joint bivariate exponential distribution of two components subjected to three types of independent exponential shocks, characterized by rates \(\lambda_1\), \(\lambda_2\), and \(\lambda_3\). The problem requires calculating the probability \(P\{X_1 > s, X_2 > t\}\), where \(X_1\) and \(X_2\) represent the failure times of components 1 and 2, respectively. The presence of type 3 shocks complicates the independence of \(X_1\) and \(X_2\). References to the works of Yan, Carpenter, and Diawara (2006) and Diawara and Carpenter (2008) provide foundational insights for solving this problem.

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Homework Statement
Consider two components and three types of shocks. A type 1 shock causes component 1 to fail, a type 2 shock causes component 2 to fail, and a type 3 shock causes both components 1 and 2 to fail. The times until shocks 1, 2, and 3 occur are independent exponential random variables with respective rates \lambda_1, \lambda_2, \lambda_3. Let X_i denote the time at which component i fails, i = 1, 2. The random variables X_1, X_2 are said to have a joint bivariate exponential distribution. Find P\{X_1 > s, X_2 > t\}.

The attempt at a solution
This problem would by so much easier if type 3 shocks didn't exists as it would make X_1, X_2 independent. Anywho...

Let Y_1, Y_2, Y_3 be the times shocks of type 1, 2, 3 occurred. I know I'm going to have to deal with the joint distribution of these three random variables. However, I can't think of anything. I need a little hint.
 
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One idea is suggested in Yan, Carpenter and Diawara (2006) and in Diawara and Carpenter (2008) in their papers from AJMMS. Please check it out, and let me know if you have questions.
 

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