Jianzhong Zhang

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Distribution Envelope Determination (DEnv) is a technique for computing descriptions of derived random variables. Derived random variables have samples that are a function of samples of other random variable(s), which are termed inputs. DEnv can compute these descriptions despite uncertainty about the precise forms of probability distributions describing(More)
This report summarizes methods to incorporate information (or lack of information) about inter-variable dependence into risk assessments that use Dempster-Shafer theory or probability bounds analysis to address epistemic and aleatory uncertainty. The report reviews techniques for simulating correlated variates for a given correlation measure and dependence(More)
Distribution Envelope Determination (DEnv) is a method for computing the CDFs of random variables whose samples are a function of samples of other random variable(s), termed inputs. DEnv computes envelopes around these CDFs when there is uncertainty about the precise form of the probability distribution describing any input. For example, inputs whose(More)
A cumulative distribution function (CDF) states the probability that a sample of a random variable will be no greater than a value x, where x is a real value. Closed form expressions for important CDFs have parameters, such as mean and variance. If these parameters are not point values but rather intervals, sharp or fuzzy, then a single CDF is not(More)
Uncertainty is a key issue in decision analysis and other kinds of applications. Researchers have developed a number of approaches to address computations on uncertain quantities. When doing arithmetic operations on random variables, an important question has to be considered: the dependency relationships among the variables. In practice, we often have(More)
Characterizing the distribution of times to failure in 2-component systems is an important special case of a more general problem, finding the distribution of a function of random variables. Advances in this area are relevant to reliability as well as other fields, and influential papers on the topic have appeared in the reliability field over a span of(More)