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Convergence in Distribution for Uncertain Random Variables
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DOI：10.1109/TFUZZ.2017.2724021.png)
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Abstract
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A random variable is a measurable function from an uncertainty space to the set of real numbers, which is used to model randomness. An uncertain variable is a measurable function from uncertainty space to the set of real numbers, which is used to describe uncertainty. However, randomness and uncertainty often simultaneously appear in a complex system. Uncertain random variable provides a useful tool to handle such a hybrid case. This concept integrates random variable and uncertain variable into a broader view. For uncertain random variables, a basic and important topic is to discuss the convergence of its sequence. Specifically, this paper focuses on studying the convergence in distribution for a sequence of uncertain random variables without a common chance distribution.
Keywords:
Chancemeasure
convergence in distribution
uncertain random variables
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