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TitleUsing second-order probabilities to make maximum entropy approach to copulas more reasonable
CreatorWu, Berlin
吳柏林
Kreinovichz, V.
Nguyen, H.T.
Contributor應數系
Key WordsCopula; Maximum entropy; Positive and negative dependence; Second-order probabilities
Date2014
Date Issued16-Jun-2015 17:35:21 (UTC+8)
SummaryCopulas 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.
RelationThai Journal of Mathematics, 2014, 1-10
Typearticle
dc.contributor 應數系-
dc.creator (作者) Wu, Berlin-
dc.creator (作者) 吳柏林zh_TW
dc.creator (作者) Kreinovichz, V.en_US
dc.creator (作者) Nguyen, H.T.en_US
dc.date (日期) 2014-
dc.date.accessioned 16-Jun-2015 17:35:21 (UTC+8)-
dc.date.available 16-Jun-2015 17:35:21 (UTC+8)-
dc.date.issued (上傳時間) 16-Jun-2015 17:35:21 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/75870-
dc.description.abstract (摘要) 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.-
dc.format.extent 176 bytes-
dc.format.mimetype text/html-
dc.relation (關聯) Thai Journal of Mathematics, 2014, 1-10-
dc.subject (關鍵詞) Copula; Maximum entropy; Positive and negative dependence; Second-order probabilities-
dc.title (題名) Using second-order probabilities to make maximum entropy approach to copulas more reasonable-
dc.type (資料類型) articleen