Finite Mixture Models for an underlying Beta distribution with an application to COVID-19 data

Reference : Finite Mixture Models for an underlying Beta distribution with an application to COVI...


	Document type :	Scientific congresses, symposiums and conference proceedings : Unpublished conference
	Discipline(s) :	Physical, chemical, mathematical & earth Sciences : Multidisciplinary, general & others
	Focus Areas :	Computational Sciences
	To cite this reference:	http://hdl.handle.net/10993/55688

Title :	Finite Mixture Models for an underlying Beta distribution with an application to COVID-19 data
Language :	English
Author, co-author :	Schiltz, Jang [University of Luxembourg > Faculty of Law, Economics and Finance (FDEF) > Department of Finance (DF) >]
	Noel, Cédric [Université de Lorraine]
Publication date :	4-Jul-2023
Peer reviewed :	Yes
On invitation :	No
Audience :	International
Event name :	34th European Meeting of Statisticians
Event date :	3.-7.7.2023
Event organizer :	Bernoulli Society for Mathematical Statistics and Probability
Event place (city) :	Warsaw
Event country :	Poland
Permalink :	http://hdl.handle.net/10993/55688

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	File	Commentary	Size	Access
Open access	Varsovie 2023.pdf	Slides of the presentation	3.91 MB	View/Open

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