Copulas

O. Strauch, V. Baláž
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引用次数: 17

Abstract

Abstract Two-dimensional distribution function g(x, y) defined in [0, 1]2 is called copula, if g(x, 1) = x and g(1,y)= y for every x, y. Similarly, s-dimensional copula is a distribution function g(x1,x2,...,xs) such that every k-dimensional face function g(1,…,1,xi1,1,…,1,xi2,1,…,1,xik,1,…,1) g\left( {1, \ldots ,1,{x_{{i_1}}},1, \ldots ,1,{x_{{i_2}}},1, \ldots ,1,{x_{{i_k}}},1, \ldots ,1} \right) is equal to xi1 xi2 ...xik for some but fixed k. In this paper we summarize and extend all known parts of copulas. In this paper we use the following abbreviations: {x} — fractional part of x; {x} — x mod 1; [x] — integer part of x; u.d. — uniform distribution; d.f. — distribution function; a.d.f. — asymptotic distribution function; u.d.p. — uniform distribution preserving; step d.f. — step distribution function; a.e. — almost everywhere; #X — cardinality of the set X.
Copulas
在[0,1]2中定义的二维分布函数g(x, y)称为copula,如果g(x, 1) = x, g(1,y)= y,对于每个x, y, s维copula是一个分布函数g(x1,x2,…,xs),使得每个k维面函数g(1,…,1,xi1,1, xi1,1,…,1,xi2,1,…,1,xik,1,…,1)g\左({1,\ldots,1,{x_{{i_1}}},1, \ldots,1,{x_{{i_2}}},1, \ldots,1,{x_{{i_k}}},1, \ldots,1,{x_{{i_2}}},1, \ldots,1,{x_{{i_k}}},1, \ldots,1},{x_{{i_k}}},1, \ldots,1},{x_{{i_k}},1, \ldots,1},{x_{i_k}},1, \ldots,1},{x_{i_k}},1}, \ldots,1},{x_{i_k}},1}, \ldots,1},{x_{i_k}},1}, \ldots,1},{x_{i_k}})等于xi1 xi2…在本文中,我们总结和推广了所有已知的copula的部分。在本文中,我们使用以下缩写:{x} - x的小数部分;{x} - x mod 1;[x] - x的整数部分;U.d .—均匀分布;d.f.—分布函数;a.d.f -渐近分布函数;保持均匀分布;Step d.f -阶跃分布函数;A.e .——几乎到处都是;#X -集合X的基数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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