Finite Mixture Models For An Underlying Beta Distribution With An Application To COVID-19 Data

SCHILTZ, Jang; NOEL, Cédric

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Finite Mixture Models For An Underlying Beta Distribution With An Application To COVID-19 Data

SCHILTZ, Jang; NOEL, Cédric

2023 • 64th world statistics congress

Peer reviewed

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https://hdl.handle.net/10993/57036

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Disciplines :

Quantitative methods in economics & management

Author, co-author :

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

NOEL, Cédric ; University of Lorraine

External co-authors :

yes

Language :

English

Title :

Finite Mixture Models For An Underlying Beta Distribution With An Application To COVID-19 Data

Publication date :

18 July 2023

Event name :

64th world statistics congress

Event organizer :

ISI

Event date :

July 17-22 , 2023

Audience :

International

Peer reviewed :

Peer reviewed

Available on ORBilu :

since 02 October 2023

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