Searcharxiv⌕ Search

arXiv subjects

Manuel Úbeda-Flores

Publications and source records attributed to Manuel Úbeda-Flores.

15 recordsLinked to original sources
arXiv2026

Concordance, symmetrization and non-exchangeability for bivariate copulas

We study the relationship between measures of non-exchangeability $μ_p$ ($p\in[1,+\infty]$), in the sense of Durante et al. (2010), and classical dependence functionals for bivariate copulas. We show that the symmetrization $C\mapsto(C+C^t)/2$ preserves Spearman's $ρ$ while annihilating $μ_p$, and that Blomqvist's $β$ carries no information about the degree of non-exchangeability. We also establish the sharp lower bound $σ(C)\ge 6\,μ_1(C)$, where $σ$ is the Schweizer-Wolff dependence measure, showing that asymmetry implies dependence. Closed-form expressions for $τ$, $ρ$, and the tail-dependence coefficients of the maximally non-exchangeable family $\{M_θ\}$ are derived as illustrations.

math.ST↗
arXiv2026

New Baire category results for stochastic orders on bivariate copulas

In the sense of Baire categories, we prove that the set of pairs of bivariate copulas that are comparable -- in either direction -- under the increasing convex order is nowhere dense in the space of all pairs of bivariate copulas equipped with the uniform metric. As a consequence, a topologically generic pair of bivariate copulas is not comparable under this order. We further extend the Baire-category programme to two additional stochastic orders on the space of bivariate copulas: the bivariate convex order and the stop-loss order on the sum of the components. For each of these orders, we establish that the set of comparable pairs is closed and nowhere dense, and we show that a topologically generic pair of bivariate copulas is simultaneously incomparable in all three orders. These results complement those obtained in [F. Durante, J. Fernández-Sánchez, C. Ignazzi (2022). Baire category results for stochastic orders. Rev. Real Acad. Cienc. Exactas Fis. Nat. Ser. A-Mat. 116, article 188] for the lower orthant order on copulas.

math.ST↗
arXiv2026

Characterizing Schur-concave commutative copulas as the closure of associative ones

Let $\mathcal{C}_a$ denote the class of associative copulas, and let $\overline{\mathcal{C}}_a$ be the closure, in the uniform metric $d_\infty$, of the convex hull of $\mathcal{C}_a$ . It is known that $\mathcal{C}_a \subseteq \mathcal{C}_{SC}$, the class of Schur-concave commutative copulas. We prove the reverse inclusion, establishing $\overline{\mathcal{C}}_a = \mathcal{C}_{SC}$.

math.ST↗
arXiv2026

Quantitative analysis of non-exchangeability in bivariate copulas: Sharp bounds, statistical tests and mixing constructions

This paper studies the degree to which a bivariate copula fails to be symmetric under coordinate permutation, a property known as non-exchangeability. Working within an axiomatic framework that quantifies this asymmetry through a family of $L^p$-based measures, we establish sharp bounds linking non-exchangeability to classical dependence and concordance measures, prove exact scaling laws under convex mixing that enable explicit construction of copulas with any prescribed degree of asymmetry, and characterise the class of maximally non-exchangeable copulas together with the feasible range of asymmetry--concordance pairs. On the inferential side, we propose a nonparametric permutation test for exchangeability with exact finite-sample error control and consistency against all asymmetric alternatives, validated by Monte Carlo simulation and illustrated on a real data set.

math.ST↗
arXiv2026

The W-footrule coefficient: A copula-based measure of countermonotonicity

We introduce the $W$-footrule coefficient $Φ_C$, a copula-based coefficient of negative association defined as the $L^1$-distance to the countermonotonic copula $W$. We prove that Gini's gamma admits the decomposition $γ_C = \frac{2}{3}(φ_C+Φ_C)$, linking it to Spearman's footrule $φ_C$. A rank-based estimator is introduced, with its strong consistency and asymptotic normality established via the functional delta method. Monte Carlo simulations confirm the estimator's finite-sample validity and its sensitivity to negative dependence structures.

math.ST↗
arXiv2026

Convex lineability in copula and quasi-copula sets

In this paper, we investigate several subsets of $n$-copulas and $n$-quasi-copulas from the perspective of convex-lineability and the recently introduced concept of convex-spaceability. Our purpose is to determine when such families contain extremely large algebraic structures, namely linearly independent sets of cardinality of the continuum whose convex hull, and in some cases a closed convex linearly independent subset, remain entirely inside the class under study. These include the families of asymmetric copulas, copulas with maximal asymmetric measure, and proper $n$-quasi-copulas, among others. In contrast, for several other natural classes of copulas we show that (maximal) convex lineability holds while convex spaceability remains an open problem.

math.ST↗
arXiv2026

Directional footrule-coefficients

Rank-based dependence measures such as Spearman's footrule are robust and invariant, but they often fail to capture directional or asymmetric dependence in multivariate settings. This paper introduces a new family of directional Spearman's footrule coefficients for multivariate data, defined within the copula framework to clearly separate marginal behavior from dependence structure. We establish their main theoretical properties, showing full consistency with the classical footrule, including behavior under independence and extreme dependence, as well as symmetry and reflection properties. Nonparametric rank-based estimators are proposed and their asymptotic consistency is discussed. Explicit expressions for several known families of copulas illustrate the ability of the proposed coefficients to detect directional dependence patterns undetected by classical measures.

math.ST↗
arXiv2025

Directional $ρ$-coefficients

In this paper we obtain advances for the concept of directional $ρ$-coefficients, originally defined for the trivariate case in [Nelsen, R.B., Úbeda-Flores, M. (2011). Directional dependence in multivariate distributions. Ann. Inst. Stat. Math 64, 677-685] by extending it to encompass arbitrary dimensions and directions in multivariate space. We provide a generalized definition and establish its fundamental properties. Moreover, we resolve a conjecture from the aforementioned work by proving a more general result applicable to any dimension, correcting a result in [García, J.E., González-López, V.A., Nelsen, R.B. (2013). A new index to measure positive dependence in trivariate distributions. J. Multivariate Anal. 115, 481-495] an erratum in the current literature. Our findings contribute to a deeper understanding of multivariate dependence and association, offering novel tools for detecting directional dependencies in high-dimensional settings. Finally, we introduce nonparametric estimators, based on ranks, for estimating directional $ρ$-coefficients from a sample.

math.ST↗
arXiv2025

Nonparametric estimation of the multivariate Spearman's footrule: a further discussion

In this paper, we propose two new estimators of the multivariate rank correlation coefficient Spearman's footrule which are based on two general estimators for Average Orthant Dependence measures. We compare the new proposals with a previous estimator existing in the literature and show that the three estimators are asymptotically equivalent, but, in small samples, one of the proposed estimators outperforms the others. We also analyse Pitman efficiency of these indices to test for multivariate independence as compared to multivariate versions of Kendall's tau and Spearman's rho.

math.ST↗
arXiv2025

Supports of quasi-copulas

It is known that for every $s\in]1,2[$ there is a copula whose support is a self-similar fractal set with Hausdorff -- and box-counting -- dimension $s$. In this paper we provide similar results for (proper) quasi-copulas, in both the bivariate and multivariate cases.

math.DS↗
arXiv2025

Total positivity and dependence of order statistics

In this comprehensive study, we delve deeply into the concept of multivariate total positivity, defining it in accordance with a direction. We rigorously explore numerous salient properties, shedding light on the nuances that characterize this notion. Furthermore, our research extends to establishing distinct forms of dependence among the order statistics of a sample from a distribution function. Our analysis aims to provide a nuanced understanding of the interrelationships within multivariate total positivity and its implications for statistical analysis and probability theory.

math.ST↗
arXiv2025

Extreme semilinear copulas

We study the extreme points (in the Krein-Milman sense) of the class of semilinear copulas and provide their characterization. Related results into the more general setting of conjunctive aggregation functions (i.e, semi--copulas and quasi--copulas) are also presented.

math.PR↗
arXiv2025

Best-possible bounds on the set of copulas with a given value of Gini's gamma

In this note, pointwise best-possible (lower and upper) bounds on the set of copulas with a given value of the Gini's gamma coefficient are established. It is shown that, unlike the best-possible bounds on the set of copulas with a given value of other known measures such as Kendall's tau, Spearman's rho or Blomqvist's beta, the bounds found are not necessarily copulas, but proper quasi-copulas.

math.ST↗
arXiv2025

Modeling directional monotonicity with copulas

The purpose of this paper is to characterize the concept of monotonicity according to a direction related to a set of n random variables in terms of its associated n-copula C. We start establishing relationships in the bivariate and trivariate cases, which help to understand the extension to the multivariate case. Examples of copulas in all the studied cases are provided.

math.ST↗