FlexMix Version 2: Finite Mixtures with Concomitant Variables and Varying and Constant Parameters
Bettina Grün and
Friedrich Leisch
Journal of Statistical Software, 2008, vol. 028, issue i04
Abstract:
flexmix provides infrastructure for flexible fitting of finite mixture models in R using the expectation-maximization (EM) algorithm or one of its variants. The functionality of the package was enhanced. Now concomitant variable models as well as varying and constant parameters for the component specific generalized linear regression models can be fitted. The application of the package is demonstrated on several examples, the implementation described and examples given to illustrate how new drivers for the component specific models and the concomitant variable models can be defined.
Date: 2008-10-06
References: View complete reference list from CitEc
Citations: View citations in EconPapers (101)
Downloads: (external link)
https://www.jstatsoft.org/index.php/jss/article/view/v028i04/v28i04.pdf
https://www.jstatsoft.org/index.php/jss/article/do ... flexmix_2.2-0.tar.gz
https://www.jstatsoft.org/index.php/jss/article/do ... ile/v028i04/v28i04.R
https://www.jstatsoft.org/index.php/jss/article/do ... v28i04-concomitant.R
https://www.jstatsoft.org/index.php/jss/article/do ... 28i04/v28i04-ziglm.R
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:jss:jstsof:v:028:i04
DOI: 10.18637/jss.v028.i04
Access Statistics for this article
Journal of Statistical Software is currently edited by Bettina Grün, Edzer Pebesma and Achim Zeileis
More articles in Journal of Statistical Software from Foundation for Open Access Statistics
Bibliographic data for series maintained by Christopher F. Baum ().