Concordance and Copulas: A Survey

By Roger B. Nelsen. 2002

81 citations recorded by the source corpus.

Subfields: Finance, Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/d7938fd1ee3430c6b1d0221d92158020e2dd5f05

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Finance

1. Martin Ruppert
2. Sandra Gaißer
3. Friedrich Schmid
4. Rafael Schmidt
5. Thomas Blumentritt
6. Petra Friederichs
7. Manuel Úbeda-Flores
8. Ali Dolati

In Management Science and Operations Research

1. Friedrich Schmid
2. Rafael Schmidt
3. Martin Ruppert
4. Sandra Gaißer
5. Ali Dolati
6. Thomas Blumentritt
7. Manuel Úbeda-Flores
8. M. D. Taylor

In Statistics and Probability

1. Martin Ruppert
2. Sandra Gaißer
3. Friedrich Schmid
4. Rafael Schmidt
5. Thomas Blumentritt
6. Ali Dolati
7. M. D. Taylor
8. Manuel Úbeda-Flores

Citations in the corpus

• On Measures of Multivariate Concordance (2006, methodology): “(Nelsen [6, 7]); and a multivariate population version of Blomqvist’s beta is given by”
• Copula-Based Measures of Multivariate Association (2010, methodology): “12) reduces to 2dC (1/2)−1 2d−1−1 , which coincides with the multivariate version originally introduced in Nelsen [78].”
• Multivariate non-normally distributed random variables in climate research - introduction to the copula approach (2008, background): “A class of copulas that allows for a wider variety of dependence structures is given by the Archimedean copulas, with the definitions from above and the function φ which is called the generator of the copula (Embrechts et al., 2001; Nelsen, 2006; Nelsen et al., 2002).”
• Multivariate versions of Blomqvist’s beta and Spearman’s footrule (2005, background): “Nelsen (2002) presents the probabili ty of concordance in terms of n-copulas: Let X1 and X2 be independent vectors of continuous random variables with common univariate margins and n-copulas C1 and C2, respectively, and let Q~n denote the probabili ty of concordance between X1 and X2, i.e., Qr n =…”
• Nonparametric inference on multivariate versions of Blomqvist’s beta and related measures of tail dependence (2007, methodology): “We mention Joe (1990), Nelsen (2002), Taskinen, Oja, and Randles (2005), and Úbeda-Flores (2005).”
• Multivariate measures of concordance (2007, methodology): “(2) In another approach, Joe (1990) and Nelsen (2002) constructed examples of measures of concordance of a different character which in some sense consider all the random variables of (X1, . . . , Xn) simultaneously.”