Zobrazeno 1 - 10
of 35
pro vyhledávání: '"SAEM-MCMC algorithm"'
Publikováno v:
XXIV International Biometric Conference, July 13-18
XXIV International Biometric Conference, July 13-18, Jul 2008, Dublin, Ireland. pp.Inconnu
XXIV International Biometric Conference, July 13-18, Jul 2008, Dublin, Ireland. pp.Inconnu
International audience
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::637e031d48f0c23f1f37d506656c3b75
https://hal.inrae.fr/hal-02823988
https://hal.inrae.fr/hal-02823988
Publikováno v:
HAL
Journal de la Société Française de Statistique
Journal de la Société Française de Statistique, Société Française de Statistique et Société Mathématique de France, 2009, 150 (2), pp.65-83
Journal de la Société Française de Statistique
Journal de la Société Française de Statistique, Société Française de Statistique et Société Mathématique de France, 2009, 150 (2), pp.65-83
The SAEM-MCMC algorithm is a powerful tool for computing maximum likelihood estimators in the wide class of nonlinear mixed effects models. We propose in this article an adaptation of this algorithm to the estimation of heterogeneous variances in suc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::c7169558d9ead2d9a746de887855968d
https://hal.archives-ouvertes.fr/hal-01193504
https://hal.archives-ouvertes.fr/hal-01193504
Autor:
Diabaté, Modibo
Publikováno v:
Modélisation et simulation. Université Grenoble Alpes, 2019. Français. ⟨NNT : 2019GREAM040⟩
This thesis is about mathematical modeling of cancer dynamics ; it is divided into two research projects.In the first project, we estimate the parameters of the deterministic limit of a stochastic process modeling the dynamics of melanoma (skin cance
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::876d0e75cd401a5340b7dc107b69a1e6
https://tel.archives-ouvertes.fr/tel-02508944/file/DIABATE_2019_archivage.pdf
https://tel.archives-ouvertes.fr/tel-02508944/file/DIABATE_2019_archivage.pdf
Autor:
Charles El-Nouty, Estelle Kuhn
Publikováno v:
Statistics and Computing
Statistics and Computing, Springer Verlag (Germany), 2013, 23 (3), pp.413-423. ⟨10.1007/s11222-012-9319-7⟩
Statistics and Computing, Springer Verlag (Germany), 2013, 23 (3), pp.413-423. ⟨10.1007/s11222-012-9319-7 ⟩
Statistics and Computing, Springer Verlag (Germany), 2013, 23 (3), pp.413-423. ⟨10.1007/s11222-012-9319-7⟩
Statistics and Computing, Springer Verlag (Germany), 2013, 23 (3), pp.413-423. ⟨10.1007/s11222-012-9319-7 ⟩
A maximum likelihood estimation procedure is presented for the frailty model. The procedure is based on a stochastic Expectation Maximization algorithm which converges quickly to the maximum likelihood estimate. The usual expectation step is replaced
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b059357bb0578502e4361e8dce0c9f53
https://hal.archives-ouvertes.fr/hal-01190284
https://hal.archives-ouvertes.fr/hal-01190284
Autor:
Kuhn, Estelle1 estelle.kuhn@jouy.inra.fr, Goethals, Klara2, El-Nouty, Charles3, Duchateau, Luc2
Publikováno v:
Journal of Agricultural, Biological & Environmental Statistics (JABES). Dec2016, Vol. 21 Issue 4, p601-618. 18p.
Akademický článek
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Akademický článek
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Publikováno v:
Statistical Methods in Medical Research; Jun2024, Vol. 33 Issue 6, p953-965, 13p
On the curved exponential family in the Stochastic Approximation Expectation Maximization Algorithm.
Autor:
Debavelaere, Vianney1 (AUTHOR) vianney.debavelaere@polytechnique.edu, Allassonnière, Stéphanie2 (AUTHOR)
Publikováno v:
ESAIM: Probability & Statistics. 7/27/2021, Vol. 25, p408-432. 25p.
Autor:
Mangin, Olivier1 (AUTHOR), Zheng, Yi2,3 (AUTHOR), Bouazza, Naïm2,4,5 (AUTHOR) naim.bouazza@aphp.fr, Foissac, Frantz2,4,5 (AUTHOR), Benaboud, Sihem2,3,5 (AUTHOR), Lui, Gabrielle2,3,5 (AUTHOR), Hirt, Déborah2,3,5 (AUTHOR), Mouthon, Luc1 (AUTHOR), Tréluyer, Jean‐Marc2,3,4,5 (AUTHOR), Urien, Saïk2,4,5 (AUTHOR)
Publikováno v:
Fundamental & Clinical Pharmacology. Apr2020, Vol. 34 Issue 2, p270-278. 9p.