Modèles de mélanges finis pour une distribution de loi BETA sous-jacente avec une application à des données sur la COVID-19

NOEL, Cédric; SCHILTZ, Jang

Unpublished conference/Abstract (Scientific congresses, symposiums and conference proceedings)

NOEL, Cédric; SCHILTZ, Jang

2022 • 27èmes Rencontres de la Société Francophone de Classification

Permalink
https://hdl.handle.net/10993/52280

Files (1)Send to Details Statistics Bibliography Similar publications

Files

Full Text

SFC2022.pdf

Author postprint (1.21 MB)

Download

All documents in ORBilu are protected by a user license.

Send to

RIS BibTex APA Chicago Permalink X Linkedin

Details

Disciplines :

Quantitative methods in economics & management

Author, co-author :

NOEL, Cédric ; University of Luxembourg > Faculty of Science, Technology and Medecine (FSTM)

SCHILTZ, Jang ; University of Luxembourg > Faculty of Law, Economics and Finance (FDEF) > Department of Finance (DF)

External co-authors :

yes

Language :

French

Title :

Modèles de mélanges finis pour une distribution de loi BETA sous-jacente avec une application à des données sur la COVID-19

Alternative titles :

[en] Finite mixture models with an underlying Beta distribution and an application to COVID-19 data

Publication date :

14 September 2022

Event name :

27èmes Rencontres de la Société Francophone de Classification

Event organizer :

SFC

Event place :

Lyon, France

Event date :

14.-16.9.2022

Audience :

International

Focus Area :

Systems Biomedicine

Available on ORBilu :

since 29 September 2022

Statistics

Number of views

72 (3 by Unilu)

Number of downloads

127 (0 by Unilu)

More statistics