Informatica logo


Login Register

  1. Home
  2. Issues
  3. Volume 13, Issue 2 (2002)
  4. Comparison of Poisson Mixture Models for ...

Informatica

Information Submit your article For Referees Help ATTENTION!
  • Article info
  • Related articles
  • More
    Article info Related articles

Comparison of Poisson Mixture Models for Count Data Clusterization
Volume 13, Issue 2 (2002), pp. 209–226
Jurgis Sušinskas   Marijus Radavičius  

Authors

 
Placeholder
https://doi.org/10.3233/INF-2002-13205
Pub. online: 1 January 2002      Type: Research Article     

Received
1 March 2002
Published
1 January 2002

Abstract

Five methods for count data clusterization based on Poisson mixture models are described. Two of them are parametric, the others are semi-parametric. The methods emlploy the plug-in Bayes classification rule. Their performance is investigated by making use of computer simulation and compared mainly by the clusterization error rate. We also apply the clusterization procedures to real count data and discuss the results.

Related articles PDF XML
Related articles PDF XML

Copyright
No copyright data available.

Keywords
count data clusterization nonparametric Poisson mixtures plug-in Bayes classification rule maximum likelihood estimator classification error rate

Metrics
since January 2020
618

Article info
views

0

Full article
views

381

PDF
downloads

164

XML
downloads

Export citation

Copy and paste formatted citation
Placeholder

Download citation in file


Share


RSS

INFORMATICA

  • Online ISSN: 1822-8844
  • Print ISSN: 0868-4952
  • Copyright © 2023 Vilnius University

About

  • About journal

For contributors

  • OA Policy
  • Submit your article
  • Instructions for Referees
    •  

    •  

Contact us

  • Institute of Data Science and Digital Technologies
  • Vilnius University

    Akademijos St. 4

    08412 Vilnius, Lithuania

    Phone: (+370 5) 2109 338

    E-mail: informatica@mii.vu.lt

    https://informatica.vu.lt/journal/INFORMATICA
Powered by PubliMill  •  Privacy policy