- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
Online-Ressource, 1 online resource.
- Sprache
-
Englisch
- Erschienen in
-
Model based clustering of multinomial count data ; day:5 ; month:7 ; year:2023 ; pages:1-47
Advances in data analysis and classification ; (5.7.2023), 1-47
- Urheber
-
Papastamoulis, Panagiotis
- Beteiligte Personen und Organisationen
-
SpringerLink (Online service)
- DOI
-
10.1007/s11634-023-00547-5
- URN
-
urn:nbn:de:101:1-2023100408451156877497
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
14.08.2025, 10:53 MESZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Papastamoulis, Panagiotis
- SpringerLink (Online service)
Ähnliche Objekte (12)
Clustering microbiome data using mixtures of logistic normal multinomial models
Testing exogeneity of multinomial regressors in count data models: does two stage residual inclusion work?
Multinomial randomized response models
Testing the multinomial logit model
Testing the Multinomial Logit Model
Counting on count data models
Semiparametric Bayesian count data models
Nonseparable multinomial choice models in cross-section and panel data
Inference on semiparametric multinomial response models
Heterogeneity in general multinomial choice models
GMM for panel count data models
General flation models for count data
Clustering microbiome data using mixtures of logistic normal multinomial models
Testing exogeneity of multinomial regressors in count data models: does two stage residual inclusion work?
Multinomial randomized response models
Testing the multinomial logit model
Testing the Multinomial Logit Model
Counting on count data models
Semiparametric Bayesian count data models
Nonseparable multinomial choice models in cross-section and panel data
Inference on semiparametric multinomial response models
Heterogeneity in general multinomial choice models
GMM for panel count data models
General flation models for count data
Clustering microbiome data using mixtures of logistic normal multinomial models
Testing exogeneity of multinomial regressors in count data models: does two stage residual inclusion work?
Multinomial randomized response models
Testing the multinomial logit model
Testing the Multinomial Logit Model
Counting on count data models
Semiparametric Bayesian count data models
Nonseparable multinomial choice models in cross-section and panel data
Inference on semiparametric multinomial response models
Heterogeneity in general multinomial choice models
GMM for panel count data models