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The associated reliability problems to be solved during the optimization process are high-dimensional (1000 or more random variables).
We consider copula modeling of the dependence between two or more random variables in the presence of a multivariate covariate.
However, (1.1) and (1.2) are not equivalent for a collection of three or more random variables.
However, (1.1) and (1.2) are not equivalent for a collection of 3 or more random variables.
An information source may also be composed of two or more random variables.
We can generalize the expectation and variance of a function of two or more random variables using Taylor series expansion.
Similar(48)
I applied the dots with an eye dropper, again to bring in a more random variable.
Uncertainty in the limit state function may be represented by introducing one or more additional random variables.
The present paper first gives a brief review of procedures to generate two or more correlated random variables with Gaussian distributions and with a given joint probability density.
Therefore Theorem 2.6 improves and extends Wu et al. [10] result (see Theorem 1.2) to the more general random variables.
Hence Theorem 2.4 improves and extends the results of Wu et al. [10] and Wang et al. [11] to the more general random variables.
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more random buttons
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