A flexible approach to finite mixture regression models for multivariate mixed responses

Author:

Alfò Marco,Rocchetti Irene

Publisher

Elsevier BV

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Reference17 articles.

1. A general maximum likelihood analysis of variance components in generalized linear models;Aitkin;Biometrics,1999

2. Testing for dependence in mixed effect models for multivariate mixed responses;Alfó,2010

3. A semiparametric mixture model for multivariate count data, with application;Alfó;Econometrics Journal,2004

4. Assessing a mixture model for clustering with the integrated completed likelihood;Biernacki;IEEE Transactions on Pattern Analysis and Machine Intelligence,2000

5. Model selection and Akaike’s information criterion (AIC): the general theory and its analytical extensions;Bozdogan;Psychometrika,1987

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1. Random effect models for multivariate mixed data: A Parafac-based finite mixture approach;Statistical Modelling;2021-09-01

2. A bidimensional finite mixture model for longitudinal data subject to dropout;Statistics in Medicine;2018-06-05

3. Over-and Underdispersion Models;Methods and Applications of Statistics in Clinical Trials;2014-06-13

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