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Finite Mixture Models for an underlying Beta distribution with an application to COVID-19 data
SCHILTZ, Jang; NOEL, Cédric
2022
 

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Disciplines :
Finance
Author, co-author :
SCHILTZ, Jang ;  University of Luxembourg > Faculty of Law, Economics and Finance (FDEF) > Department of Finance (DF)
NOEL, Cédric ;  University of Luxembourg > Faculty of Science, Technology and Medecine (FSTM) ; University of Lorraine
Language :
English
Title :
Finite Mixture Models for an underlying Beta distribution with an application to COVID-19 data
Publication date :
18 April 2022
Version :
1
Number of pages :
31
Focus Area :
Computational Sciences
Available on ORBilu :
since 05 May 2022

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