Inducing a Target Association between Ordinal Variables by Using a Parametric Copula Family
The need for building and generating statistically dependent random variables arises in various fields of study where simulation has proven to be a useful tool. In this work, we present an approach for constructing ordinal variables with arbitrarily assigned marginal distributions and value of asso...
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| Language: | English |
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Austrian Statistical Society
2020-04-01
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| Series: | Austrian Journal of Statistics |
| Online Access: | http://www.ajs.or.at/index.php/ajs/article/view/1116 |
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doaj-624293e9a7384632acb4d90dd894445f2021-04-22T12:31:55ZengAustrian Statistical SocietyAustrian Journal of Statistics1026-597X2020-04-0149410.17713/ajs.v49i4.1116Inducing a Target Association between Ordinal Variables by Using a Parametric Copula FamilyAlessandro Barbiero0Universit`a degli Studi di Milano The need for building and generating statistically dependent random variables arises in various fields of study where simulation has proven to be a useful tool. In this work, we present an approach for constructing ordinal variables with arbitrarily assigned marginal distributions and value of association or correlation, expressed in terms of either Goodman and Kruskal's gamma or Pearson's linear correlation. The approach first constructs a class of bivariate copula-based distributions matching the assigned margins, and then, within this class, identifies the distribution matching the assigned association or correlation, by calibrating the copula parameter. A numerical example and a possible application are illustrated. http://www.ajs.or.at/index.php/ajs/article/view/1116 |
| collection |
DOAJ |
| language |
English |
| format |
Article |
| sources |
DOAJ |
| author |
Alessandro Barbiero |
| spellingShingle |
Alessandro Barbiero Inducing a Target Association between Ordinal Variables by Using a Parametric Copula Family Austrian Journal of Statistics |
| author_facet |
Alessandro Barbiero |
| author_sort |
Alessandro Barbiero |
| title |
Inducing a Target Association between Ordinal Variables by Using a Parametric Copula Family |
| title_short |
Inducing a Target Association between Ordinal Variables by Using a Parametric Copula Family |
| title_full |
Inducing a Target Association between Ordinal Variables by Using a Parametric Copula Family |
| title_fullStr |
Inducing a Target Association between Ordinal Variables by Using a Parametric Copula Family |
| title_full_unstemmed |
Inducing a Target Association between Ordinal Variables by Using a Parametric Copula Family |
| title_sort |
inducing a target association between ordinal variables by using a parametric copula family |
| publisher |
Austrian Statistical Society |
| series |
Austrian Journal of Statistics |
| issn |
1026-597X |
| publishDate |
2020-04-01 |
| description |
The need for building and generating statistically dependent random variables arises in various fields of study where simulation has proven to be a useful tool.
In this work, we present an approach for constructing ordinal variables with arbitrarily assigned marginal distributions and value of association or correlation, expressed in terms of either Goodman and Kruskal's gamma or Pearson's linear correlation.
The approach first constructs a class of bivariate copula-based distributions matching the assigned margins, and then, within this class, identifies the distribution matching the assigned association or correlation, by calibrating the copula parameter. A numerical example and a possible application are illustrated.
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| url |
http://www.ajs.or.at/index.php/ajs/article/view/1116 |
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AT alessandrobarbiero inducingatargetassociationbetweenordinalvariablesbyusingaparametriccopulafamily |
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