Marshall–Olkin exponential distribution

Marshall–Olkin exponential

Support	${\displaystyle x\in [0,\infty )^{b}}$

In applied statistics, the Marshall–Olkin exponential distribution is any member of a certain family of continuous multivariate probability distributions with positive-valued components. It was introduced by Albert W. Marshall and Ingram Olkin.^[1] One of its main uses is in reliability theory, where the Marshall–Olkin copula models the dependence between random variables subjected to external shocks. ^{[2] [3] [4]}

Definition

Let ${\displaystyle \{E_{B}:\varnothing \neq B\subset \{1,2,\ldots ,b\}\}}$ be a set of independent, exponentially distributed random variables, where ${\displaystyle E_{B}}$ has mean ${\displaystyle 1/\lambda _{B}}$. Let

${\displaystyle T_{j}=\min\{E_{B}:j\in B\},\ \ j=1,\ldots ,b.}$

The joint distribution of ${\displaystyle T=(T_{1},\ldots ,T_{b})}$ is called the Marshall–Olkin exponential distribution with parameters ${\displaystyle \{\lambda _{B},B\subset \{1,2,\ldots ,b\}\}.}$

Concrete example

Suppose b = 3. Then there are seven nonempty subsets of { 1, ..., b } = { 1, 2, 3 }; hence seven different exponential random variables:

${\displaystyle E_{\{1\}},E_{\{2\}},E_{\{3\}},E_{\{1,2\}},E_{\{1,3\}},E_{\{2,3\}},E_{\{1,2,3\}}}$

Then we have:

${\displaystyle {\begin{aligned}T_{1}&=\min\{E_{\{1\}},E_{\{1,2\}},E_{\{1,3\}},E_{\{1,2,3\}}\}\\T_{2}&=\min\{E_{\{2\}},E_{\{1,2\}},E_{\{2,3\}},E_{\{1,2,3\}}\}\\T_{3}&=\min\{E_{\{3\}},E_{\{1,3\}},E_{\{2,3\}},E_{\{1,2,3\}}\}\\\end{aligned}}}$

References

1. Marshall, Albert W.; Olkin, Ingram (1967), "A multivariate exponential distribution", Journal of the American Statistical Association, 62 (317): 30–49, doi:10.2307/2282907, JSTOR 2282907, MR 0215400
2. Barrera, J.; Cancela, H.; Moreno, E. (2015), "Topological optimization of reliable networks under dependent failures", Operations Research Letters, 43 (2): 132–136, doi:10.1016/j.orl.2014.12.014
3. Botev, Z.; L'Ecuyer, P.; Simard, R.; Tuffin, B. (2016), "Static network reliability estimation under the Marshall-Olkin copula", ACM Transactions on Modeling and Computer Simulation, 26 (2): No.14, doi:10.1145/2775106, S2CID 16677453
4. Durante, F.; Girard, S.; Mazo, G. (2016), "Marshall--Olkin type copulas generated by a global shock", Journal of Computational and Applied Mathematics, 296: 638–648, doi:10.1016/j.cam.2015.10.022

• Xu M, Xu S. "An Extended Stochastic Model for Quantitative Security Analysis of Networked Systems". Internet Mathematics, 2012, 8(3): 288–320.