Quantile functions for multivariate analysis: approaches and applications

By Robert Serfling. 2002

245 citations recorded by the source corpus.

Subfields: Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/327e90bb6a53350ad5a2288d9aee2b339770a76c

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

Multivariate quantiles in hydrological frequency analysis (2011, methodology): “Serfling (2002) presented a review and a classification of some of these multivariate quantile versions.”
Bivariate Flood Frequency Analysis with Historical Information Based on Copula (2013, background): “Several efforts have been spent on the issue of multivariate quantiles (Serfling 2002; Belzunce et al. 2007; Chebana and Quarda 2011; Salvadori et al. 2011).”
Nonparametric Multivariate Descriptive Measures Based on Spatial Quantiles (2004, background): “For extension to the multivariate case, one must select a particular version of multivariate quantiles (see Serfling, 2002b, for a partial review of various ad hoc notions).”
Monge-Kantorovich Depth, Quantiles, Ranks and Signs (2014, methodology): “In this paper, we take a totally different and more agnostic approach, on the model of the discussion by Serfling in [51]: if the ultimate purpose of statistical depth is to provide, for each distribution P , a P -related ordering of IRd producing adequate concepts of quantile and distribution funct”
A Depth Function and a Scale Curve Based on Spatial Quantiles (2002, methodology): “The validity of (12) follows under conditions A1–A3 of Theorem 3.1 of Serfling (2002a).”
NONPARAMETRIC FRONTIER ESTIMATION: A CONDITIONAL QUANTILE-BASED APPROACH (2005, background): “Serfling (2001) stated, “Despite the absence of a natural ordering of Euclidean space for dimension greater than one, effort to define vector-valued quantile functions for multivariate distributions has generated several approaches”.”
An Approach to Multivariate Covariate-Dependent Quantile Contours With Application to Bivariate Conditional Growth Charts (2008, methodology): “Serfling (2002) presented a nice survey of multivariate quantile functions and outlined the probabilistic properties that a multivariate quantile function should have.”
Distribution and quantile functions, ranks and signs in dimension d: A measure transportation approach (2021, background): “…ranks have been considered in Liu (1992), Liu and Singh (1993), He and Wang (1997), Zuo and He (2006), Zuo and Serfling (2000), among others; see Serfling (2002) for a general introduction on statistical depth, Hallin et al. (2010) for the related concept of quantile, Lòpez-Pintado and Romo…”
Testing Multivariate Economic Restrictions Using Quantiles: The Example of Slutsky Negative Semidefiniteness (2011, background): “In addition to the stochastic regressors, the DGP contains random heterogeneity parameters A = (A0; A1; A2; A3; A4) 0, independent of P; for which we specify that A N ( A; A) : We choose A = (20; 20; 20; 30; 10)0; the second to fourth reproduce the average absolute values of the own price e¤ects of ”
Asymmetry and Gradient Asymmetry Functions: Density‐Based Skewness and Kurtosis (2008, background): “Considerations of the notion of depth (Serfling, 2002, 2004, and references therein) might be useful in understanding these ideas more deeply.”
On the return period and design in a multivariate framework (2011, background): “Recently, several efforts have been spent on the issues of multivariate design and quantiles (see, e.g. Serﬂing, 2002; Belzunce et al. , 2007; Chebana and Ouarda, 2009, 2011b; Chaouch and Goga , 2010, and references therein; for a methodology to identify multivariate extremes by using depth…”