Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Emilie Chautru"'
Publikováno v:
ESAIM: Probability and Statistics
ESAIM: Probability and Statistics, EDP Sciences, 2019, 23, pp.310-337. ⟨10.1051/ps/2018021⟩
ESAIM: Probability and Statistics, 2019, 23, pp.310-337. ⟨10.1051/ps/2018021⟩
ESAIM: Probability and Statistics, EDP Sciences, 2019, 23, pp.310-337. ⟨10.1051/ps/2018021⟩
ESAIM: Probability and Statistics, 2019, 23, pp.310-337. ⟨10.1051/ps/2018021⟩
Iterative stochastic approximation methods are widely used to solve M-estimation problems, in the context of predictive learning in particular. In certain situations that shall be undoubtedly more and more common in the Big Data era, the datasets ava
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7e7e417adda9af30a727bca447aa6999
https://hal.archives-ouvertes.fr/hal-02078108
https://hal.archives-ouvertes.fr/hal-02078108
Autor:
Nicolas Flipo, Jean-Marie Mouchel, Cédric Fisson, Shuaitao Wang, Marion Le Gall, Sophie Ayrault, Pierre Labadie, Johnny Gasperi, Sophie Guillon, Hélène Budzinski, Evrard, O., Thomas Romary, Emilie Chautru, Déborah Abhervé, Gaëlle Chevillotte, J-B, Narcy, Aline Cattan, Michel Meybeck
Publikováno v:
Nicolas Flipo, Jean-Marie Mouchel, Cédric Fisson. Programme Interdisciplinaire de Recherche sur l'eau et l'environnement du bassin de la Seine (PIREN Seine), 2018, 978-2-490463-05-03
HAL
HAL
International audience
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::e119fe00dd7f728d46b103e2871bb6db
https://hal.science/hal-01897066/document
https://hal.science/hal-01897066/document
Publikováno v:
Scandinavian Journal of Statistics
Scandinavian Journal of Statistics, Wiley, 2017, 44 (1), pp.97-111. ⟨10.1111/sjos.12243⟩
Scandinavian Journal of Statistics, Wiley, 2016, 44 (1), pp.97-111. ⟨10.1111/sjos.12243⟩
Scandinavian Journal of Statistics, 2016, 44 (1), pp.97-111. ⟨10.1111/sjos.12243⟩
Scandinavian Journal of Statistics, Wiley, 2017, 44 (1), pp.97-111. ⟨10.1111/sjos.12243⟩
Scandinavian Journal of Statistics, Wiley, 2016, 44 (1), pp.97-111. ⟨10.1111/sjos.12243⟩
Scandinavian Journal of Statistics, 2016, 44 (1), pp.97-111. ⟨10.1111/sjos.12243⟩
International audience; It is the main purpose of this paper to study the asymptotics of certain variants of the empirical process in the context of survey data. Precisely, Functional Central Limit Theorems are established under usual conditions when
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::51ccc0722a6759db5253f1e698ffd8dc
https://hal.telecom-paristech.fr/hal-02107503
https://hal.telecom-paristech.fr/hal-02107503
Publikováno v:
Geostatistics Valencia 2016 ISBN: 9783319468181
Geostatistics Valencia 2016, Springer International Publishing
Geostats2016-10th International Geostatistics Congress
Geostats2016-10th International Geostatistics Congress, Sep 2016, Valencia, Spain. pp.459--474, ⟨10.1007/978-3-319-46819-8_31⟩
Geostatistics Valencia 2016, Springer International Publishing
Geostats2016-10th International Geostatistics Congress
Geostats2016-10th International Geostatistics Congress, Sep 2016, Valencia, Spain. pp.459--474, ⟨10.1007/978-3-319-46819-8_31⟩
Petroleum reservoir geological models are usually built in two steps. First, a 3-D model of geological bodies is computed, within which rock properties are expected to be stationary and to have low variability. Such geological domains are referred to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7b3fa8a0ea68d488456522d8849ef731
https://doi.org/10.1007/978-3-319-46819-8_31
https://doi.org/10.1007/978-3-319-46819-8_31
Publikováno v:
Statistics
Statistics, Taylor & Francis: STM, Behavioural Science and Public Health Titles, 2016, 51 (1), pp.30-42. ⟨10.1080/02331888.2016.1259810⟩
Statistics, Taylor & Francis: STM, Behavioural Science and Public Health Titles, 2017, 51 (1), pp.30-42. ⟨10.1080/02331888.2016.1259810⟩
Statistics, 2016, 51 (1), pp.30-42. ⟨10.1080/02331888.2016.1259810⟩
Statistics, Taylor & Francis: STM, Behavioural Science and Public Health Titles, 2016, 51 (1), pp.30-42. ⟨10.1080/02331888.2016.1259810⟩
Statistics, Taylor & Francis: STM, Behavioural Science and Public Health Titles, 2017, 51 (1), pp.30-42. ⟨10.1080/02331888.2016.1259810⟩
Statistics, 2016, 51 (1), pp.30-42. ⟨10.1080/02331888.2016.1259810⟩
International audience; In certain situations that shall be undoubtedly more and more common in the Big Data era, the datasets available are so massive that computing statistics over the full samples is hardly feasible, if not unfeasible. A natural a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6db16bc38a6b3b17915915bdddb9b5a5
https://hal.telecom-paristech.fr/hal-02107516
https://hal.telecom-paristech.fr/hal-02107516
Publikováno v:
IEEE transactions on big data
IEEE transactions on big data, IEEE, 2015, ⟨10.1109/BigData.2014.7004208⟩
BigData Conference
IEEE transactions on big data, 2015, ⟨10.1109/BigData.2014.7004208⟩
IEEE transactions on big data, IEEE, 2015, ⟨10.1109/BigData.2014.7004208⟩
BigData Conference
IEEE transactions on big data, 2015, ⟨10.1109/BigData.2014.7004208⟩
In certain situations that shall be undoubtedly more and more common in the Big Data era, the datasets available are so massive that computing statistics over the full sample is hardly feasible, if not unfeasible. A natural approach in this context c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1ae41e2d093b83e41949aed4814427f9
https://hal.archives-ouvertes.fr/hal-01707390
https://hal.archives-ouvertes.fr/hal-01707390
Publikováno v:
ESAIM: Probability and Statistics
ESAIM: Probability and Statistics, 2015, 19, pp.28-59. ⟨10.1051/ps/2014011⟩
ESAIM: Probability and Statistics, EDP Sciences, 2015, 19, pp.28-59. ⟨10.1051/ps/2014011⟩
ESAIM: Probability and Statistics, 2015, 19, pp.28-59. ⟨10.1051/ps/2014011⟩
ESAIM: Probability and Statistics, EDP Sciences, 2015, 19, pp.28-59. ⟨10.1051/ps/2014011⟩
International audience; This paper is devoted to tail index estimation in the context of survey data. Assuming that the population of interest is described by a heavy-tailed statistical model, we prove that the survey scheme plays a crucial role in t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::976b06749e89b007dbfc17a57e4e791f
https://hal.science/hal-01468900
https://hal.science/hal-01468900