{"title":"Copulas","authors":"O. Strauch, V. Baláž","doi":"10.2478/udt-2023-0009","DOIUrl":null,"url":null,"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.","PeriodicalId":23390,"journal":{"name":"Uniform distribution theory","volume":"76 1","pages":"147 - 200"},"PeriodicalIF":0.0000,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":"{\"title\":\"Copulas\",\"authors\":\"O. Strauch, V. Baláž\",\"doi\":\"10.2478/udt-2023-0009\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":23390,\"journal\":{\"name\":\"Uniform distribution theory\",\"volume\":\"76 1\",\"pages\":\"147 - 200\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"17\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Uniform distribution theory\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2478/udt-2023-0009\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Uniform distribution theory","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2478/udt-2023-0009","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.