Results 1 to 10 of about 146 (91)

Hoeffding–Sobol decomposition of homogeneous co-survival functions: from Choquet representation to extreme value theory application [PDF]

Dependence Modeling, 2021
The paper investigates the Hoeffding–Sobol decomposition of homogeneous co-survival functions. For this class, the Choquet representation is transferred to the terms of the functional decomposition, and in addition to their individual variances, or to ...
Mercadier Cécile, Ressel Paul
doaj   +4 more sources

Linking the Hoeffding–Sobol and Möbius formulas through a decomposition of Kuo, Sloan, Wasilkowski, and Woźniakowski [PDF]

Statistics and Probability Letters, 2022
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Cecile Mercadier, Olivier Roustant, Christian Genest   +2 more
exaly   +5 more sources

Generalized Hoeffding-Sobol decomposition for dependent variables - application to sensitivity analysis

Electronic Journal of Statistics, 2012
In this paper, we consider a regression model built on dependent variables. This regression modelizes an input output relationship. Under boundedness assumptions on the joint distribution function of the input variables, we show that a generalized Hoeffding-Sobol decomposition is available.
Fabrice Gamboa, Christophe Prieur
exaly   +7 more sources

Hoeffding-ANOVA decompositions for symmetric statistics of exchangeable observations

Annals of Probability, 2004
Published by the Institute of Mathematical Statistics (http://www.imstat.org) in the Annals of Probability (http://www.imstat.org/aop/) at http://dx.doi.org/10.1214 ...
Giovanni Peccati
exaly   +6 more sources

Hoeffding decompositions and urn sequences

Annals of Probability, 2008
Let \({\mathbf X}= X_1,X_2,\dots\) be an infinite exchangeable sequence of \(D\)- valued random variables, with \(D= \{d_1,\dots, d_m\}\). Let \(SU_0(X_1,\dots, X_n)= R\) and \(SU_k\), \(k= 1,\dots, n\), be the space of all random variables \[ F(X_1,\dots, X_n)= \sum\varphi(X_{j1},\dots, X_{jk})\tag{1} \] with sum over all \(1\leq j_1 1\) and \(k= 1 ...
Omar El-Dakkak, Giovanni Peccati
exaly   +4 more sources

Hoeffding decomposition of functions of random dependent variables

Journal of Multivariate Analysis
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Marouane Il Idrissi, Nicolas Bousquet, Fabrice Gamboa   +2 more
exaly   +4 more sources

Hoeffding decomposition in $$H^1$$ spaces [PDF]

Mathematische Zeitschrift, 2020
Abstract The well known result of Bourgain and Kwapień states that the projection $$P_{\le m}$$ P ≤ m onto the subspace of the Hilbert space $$L^2\left( \Omega ^\infty \right) $$ L 2 Ω ∞ spanned by functions dependent on at most m variables is bounded in $$L^p$$ L p with norm $$\le c_p^m$$ ≤ c p m for $$1<p<\infty $$ 1 <
Rzeszut, Maciej, Wojciechowski, Michał
openaire   +2 more sources

RKHSMetaMod: An R Package to Estimate the Hoeffding Decomposition of a Complex Model by Solving RKHS Ridge Group Sparse Optimization Problem

The R Journal, 2022
arXiv admin note: text overlap with arXiv:1701 ...
Kamari, Halaleh, Huet, Sylvie, Taupin, Marie-Luce   +2 more
openaire   +5 more sources

Hoeffding decomposition of black-box models with dependent inputs

, 2023
Performing an additive decomposition of arbitrary functions of random elements is paramount for global sensitivity analysis and, therefore, the interpretation of black-box models. The well-known seminal work of Hoeffding characterized the summands in such a decomposition in the particular case of mutually independent inputs.
Idrissi, Marouane Il, Bousquet, Nicolas, Gamboa, Fabrice, Iooss, Bertrand, Loubes, Jean-Michel   +4 more
openaire   +2 more sources

Orthogonal decomposition of finite population L-statistics

Lietuvos Matematikos Rinkinys, 2009
In this paper we study orthogonal decomposition of finite population L-statistics. We propose quite simple form of first two terms of such decomposition.
Andrius Čiginas
doaj   +1 more source