Výsledky vyhledávání - "Muller-Gueudin A"

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A statistical methodology to select covariates in high-dimensional data under dependence. Application to the classification of genetic profiles in oncology

Autor: Bastien, Bérangère, Boukhobza, Taha, Dumond, Hélène, Gégout-Petit, Anne, Muller-Gueudin, Aurélie, Thiébaut, Charlène

We propose a new methodology for selecting and ranking covariates associated with a variable of interest in a context of high-dimensional data under dependence but few observations. The methodology successively intertwines the clustering of covariate

Externí odkaz: http://arxiv.org/abs/1909.05481

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Optimal choice among a class of nonparametric estimators of the jump rate for piecewise-deterministic Markov processes

Autor: Azaïs, Romain, Muller-Gueudin, Aurélie

A piecewise-deterministic Markov process is a stochastic process whose behavior is governed by an ordinary differential equation punctuated by random jumps occurring at random times. We focus on the nonparametric estimation problem of the jump rate f

Externí odkaz: http://arxiv.org/abs/1506.07722

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Certainty bands for the conditional cumulative distribution function and applications

Autor: Ferrigno, Sandie, Foliguet, Bernard, Maumy-Bertrand, Myriam, Muller-Gueudin, Aurélie

In this paper, we establish uniform asymptotic certainty bands for the conditional cumulative distribution function. To this aim, we give exact rate of strong uniform consistency for the local linear estimator of this function. The corollaries of thi

Externí odkaz: http://arxiv.org/abs/1407.4909

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Mod\'elisation de r\'eseaux de r\'egulation de g\`enes par processus d\'eterministes par morceaux

Autor: Muller-Gueudin, Aurélie

The molecular evolution in a gene regulatory network is classically modeled by Markov jump processes. However, the direct simulation of such models is extremely time consuming. Indeed, even the simplest Markovian model, such as the production module

Externí odkaz: http://arxiv.org/abs/1211.6539

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A statistical methodology to select covariates in high-dimensional data under dependence. Application to the classification of genetic profiles in oncology

Autor: Hélène Dumond, Charlène Thiébaut, Taha Boukhobza, Bérangère Bastien, Aurélie Muller-Gueudin, Anne Gégout-Petit

Publikováno v: Journal of Applied Statistics
Journal of Applied Statistics, Taylor & Francis (Routledge), In press, pp.23. ⟨10.1080/02664763.2020.1837083⟩
Journal of Applied Statistics, 2022, 49 (3), pp.764-781. ⟨10.1080/02664763.2020.1837083⟩
J Appl Stat

International audience; We propose a new methodology for selecting and ranking covariates associated with a variable of interest in a context of high-dimensional data under dependence but few observations. The methodology successively intertwines the

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::33f756a360f36f8b6b21ba6a5a740dea
https://doi.org/10.1080/02664763.2020.1837083

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Modeling of gene regulation networks by deterministic processes by pieces

Autor: Muller-Gueudin, Aurélie, Debussche, Arnaud, Crudu, Alina

Publikováno v: Journée de la Fédération Charles Hermite
Journée de la Fédération Charles Hermite, Jun 2019, Vandoeuvre-les-Nancy, France. pp.1-37

International audience

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::9f129b75ab2b48ef66b2b6b9cfaa4f21
https://hal.archives-ouvertes.fr/hal-02360992

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Aggregation of statistical methods for the selection of correlated variables, in large dimension

Autor: Muller-Gueudin, Aurélie, Gégout-Petit, Anne

Publikováno v: JdS 2019-51emes Journées de Statistique de la SFDS
JdS 2019-51emes Journées de Statistique de la SFDS, Jun 2019, Vandoeuvre-les-Nancy, France

International audience

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::1f5faf30e670e74f1a2fc5d0e6cc34fb
https://hal.archives-ouvertes.fr/hal-02360974/file/expose_JDS_Nancy_7juin2019.pdf

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Nested structure of intraspecific competition network in Carnobacterium maltaromaticum

Autor: Ramia, Nancy E., Mangavel, Cécile, Gaiani, Claire, Muller-Gueudin, Aurélie, Taha, Samir, Revol-Junelles, Anne-Marie, Borges, Frédéric

Publikováno v: Scientific Reports
Scientific Reports, Nature Publishing Group, 2020, 10 (1), pp.1-9. ⟨10.1038/s41598-020-63844-5⟩
Scientific Reports, 2020, 10 (1), pp.1-9. ⟨10.1038/s41598-020-63844-5⟩
Scientific Reports, Vol 10, Iss 1, Pp 1-9 (2020)

International audience; While competition targeting food-borne pathogens is being widely documented, few studies have focused on competition among non-pathogenic food bacteria. Carnobacterium maltaromaticum is a genetically diverse lactic acid bacter

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=pmid_dedup__::f03873d21df17e3b3fc2b02fd2d94f77
https://hal.univ-lorraine.fr/hal-02573667/document

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