Kendall distribution functions

By Roger B. Nelsen, J. Quesada-Molina, J. -. Rodríguez-Lallena, Manuel Úbeda-Flores. 2003

114 citations recorded by the source corpus.

Subfields: Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/3fc4067ae0bea4b4deef7f0b1361b2f084bdd08f

How researchers see this paper

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

In Management Science and Operations Research

In Statistics and Probability

Citations in the corpus

On the return period and design in a multivariate framework (2011, result): “Now, in view of the results outlined in Nelsen et al. (2001, 2003), it is immediate to show that where ν F is the probability measure induced by F over R d , and K C is the Kendall’s distribution function associated with C (see Eq.”
Everything You Always Wanted to Know about Copula Modeling but Were Afraid to Ask (2007, methodology): “For 358 / JOURNAL OF HYDROLOGIC ENGINEERING © ASCE / JULY/AUGUS additional information about the BIPIT and its properties and applications, refer to Genest and Rivest 2001 and Nelsen et al. 2003 .”
A multivariate copula‐based framework for dealing with hazard scenarios and failure probabilities (2016, unknown): “…relations can be stated: aKuðC1Þ aKuðC2Þ () KC2ðt2Þ KC1ðt1Þ; (29) and a K u ðĈ1Þ a K u ðĈ2Þ () KĈ2ðt2Þ KĈ1ðt1Þ: (30) Note that, in general, [Cap era a et al., 1997; Nelsen et al., 2003], the ordering among Kendall functions does not imply (and neither it is implied) by the POD ordering among…”
Hierarchical Kendall copulas: Properties and inference (2012, background): “d by Genest and Rivest (1993) in the bivariate case and in more detail by Barbe et al. (1996). Other accounts on it can be found, amongst others, in Imlahi et al. (1999), Genest and Rivest (2001) and Nelsen et al. (2003) as well as in the copula goodness-of-t literature (see, e.g., Wang and Wells (2”
A copula-based joint deficit index for droughts. (2010, methodology): “In this context, Kendall distribution function KC (Nelsen et al., 2003; Nelson, 2006) that is defined as the probability measure of the set fðU1; . . . ;UdÞ 2 ½0;1 dj CU1 ;...”
On the construction of multivariate extreme value models via copulas (2009, methodology): “W = C(U, V ) (Barbe et al., 1996; Genest and Rivest, 2001; Nelsen et al., 2003), it is possible to check whether the three copulas investigated provide suitable approximations by means of a Kolmogorov–Smirnov test: the results are reported in Table 2.”
Inference in multivariate Archimedean copula models (2011, background): “is the Kendall distribution function (Barbe et al. 1996; Genest and Rivest 2001; Nelsen et al. 2003 ).”
Copulas: A Review and Recent Developments (2006, methodology): “Nelsen et al.[97] have used Bertino family of copulas to show the following results relating Bertino copula and associated Kendall distribution (i.”