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Title: Using second-order probabilities to make maximum entropy approach to copulas more reasonable
Authors: Wu, Berlin
Kreinovichz, V.
Nguyen, H.T.
Contributors: 應數系
Keywords: Copula;Maximum entropy;Positive and negative dependence;Second-order probabilities
Date: 2014
Issue Date: 2015-06-16 17:35:21 (UTC+8)
Abstract: Copulas are a general way of describing dependence between two or more random variables. When we only have partial information about the dependence, i.e., when several different copulas are consistent with our knowledge, it is often necessary to select one of these copulas. A frequently used method of selecting this copula is the maximum entropy approach, when we select a copula with the largest entropy. However, in some cases, the maximum entropy approach leads to an unreasonable selection – e.g., even if we know that the two random variables are positively correlated, the maximum entropy approach completely ignores this information. In this paper, we show how to properly modify the maximum entropy approach so that it will lead to more reasonable results: by applying this approach not to the probabilities themselves, but to “second order” probabilities – i.e., probabilities of different probability distributions.
Relation: Thai Journal of Mathematics, 2014, 1-10
Data Type: article
Appears in Collections:[應用數學系] 期刊論文

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