Login
EN
[EN] English
[FR] Français
Login
EN
[EN] English
[FR] Français
Give us feedback
Search and explore
Search
Explore ORBilu
Open Science
Open Science
Open Access
Research Data Management
Definitions
Love My Data 11 - 15 Mar 2024
Statistics
Help
User Guide
FAQ
Publication list
Document types
Training
Legal Information
Data protection
Legal notices
About
About ORBilu
Deposit Mandate
ORBilu team
Impact and visibility
About statistics
About metrics
OAI-PMH
Project history
Back
Home
Detailled Reference
Request a copy
Eprint first made available on ORBilu (E-prints, Working papers and Research blog)
Finite Mixture Models for an underlying Beta distribution with an application to COVID-19 data
Schiltz, Jang
;
Noel, Cédric
2022
Permalink
https://hdl.handle.net/10993/50948
Files (1)
Send to
Details
Statistics
Bibliography
Similar publications
Files
Full Text
COVID.pdf
Author postprint (4.95 MB)
Request a copy
All documents in ORBilu are protected by a
user license
.
Send to
RIS
BibTex
APA
Chicago
Permalink
X
Linkedin
copy to clipboard
copied
Details
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
Statistics
Number of views
80 (5 by Unilu)
Number of downloads
62 (3 by Unilu)
More statistics
Bibliography
Similar publications
Contact ORBilu
