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Titlebook: An Introduction to Copulas; Roger B. Nelsen Book 19991st edition Springer Science+Business Media New York 1999 Parametric statistics.mathe

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樓主: 威風(fēng)
11#
發(fā)表于 2025-3-23 11:53:48 | 只看該作者
Definitions and Basic Properties,tribution functions” and as “distribution functions whose one-dimensional margins are uniform.” But neither of these statements is a definition—hence we will devote this chapter to giving a precise definition of copulas and to examining some of their elementary properties.
12#
發(fā)表于 2025-3-23 15:37:38 | 只看該作者
Methods of Constructing Copulas,tions with whatever marginal distributions we desire. Clearly this can be useful in modeling and simulation. Furthermore, by virtue of Theorem 2.4.3, the nonparametric nature of the dependence between two random variables, is expressed by the copula. Thus the study of concepts and measures of nonpar
13#
發(fā)表于 2025-3-23 18:20:43 | 只看該作者
14#
發(fā)表于 2025-3-24 01:00:10 | 只看該作者
15#
發(fā)表于 2025-3-24 04:47:32 | 只看該作者
Additional Topics,the subject. The original question whose answer leads to the Fréchet-Hoeffding bounds (2.5.1) is: Of all joint distribution functions . constrained to have . and ., which is the “l(fā)argest,” and which the “smallest”? Another example, which also involves optimization when the margins are fixed, is the
16#
發(fā)表于 2025-3-24 07:09:29 | 只看該作者
https://doi.org/10.1007/978-3-642-48438-4tribution functions” and as “distribution functions whose one-dimensional margins are uniform.” But neither of these statements is a definition—hence we will devote this chapter to giving a precise definition of copulas and to examining some of their elementary properties.
17#
發(fā)表于 2025-3-24 11:04:54 | 只看該作者
https://doi.org/10.1007/978-3-642-48438-4tions with whatever marginal distributions we desire. Clearly this can be useful in modeling and simulation. Furthermore, by virtue of Theorem 2.4.3, the nonparametric nature of the dependence between two random variables, is expressed by the copula. Thus the study of concepts and measures of nonpar
18#
發(fā)表于 2025-3-24 16:35:47 | 只看該作者
Die Rasse-Intelligenz-Kontroverse, reasons: (1) The ease with which they can be constructed; (2) The great variety of families of copulas which belong to this class; and (3) The many nice properties possessed by the members of this class. As mentioned in the Introduction, Archimedean copulas originally appeared not in statistics, bu
19#
發(fā)表于 2025-3-24 21:36:43 | 只看該作者
20#
發(fā)表于 2025-3-25 02:19:21 | 只看該作者
,Soziale Reaktionen auf Unmündigkeit,the subject. The original question whose answer leads to the Fréchet-Hoeffding bounds (2.5.1) is: Of all joint distribution functions . constrained to have . and ., which is the “l(fā)argest,” and which the “smallest”? Another example, which also involves optimization when the margins are fixed, is the
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