References in zbMATH (referenced in 12 articles , 2 standard articles )

Showing results 1 to 12 of 12.
Sorted by year (citations)

  1. Cavalcante, Carolina V.; Gonçalves, Kelly C. M.: Mixture models applied to heterogeneous populations (2018)
  2. Hughes, David M.; El Saeiti, Riham; García-Fiñana, Marta: A comparison of group prediction approaches in longitudinal discriminant analysis (2018)
  3. Tang, Niansheng; Wu, Ying; Chen, Dan: Semiparametric Bayesian analysis of transformation linear mixed models (2018)
  4. Xu, Peirong; Peng, Heng; Huang, Tao: Unsupervised learning of mixture regression models for longitudinal data (2018)
  5. Su, Steve: Flexible modelling of survival curves for censored data (2016)
  6. Cecile Proust-Lima, Viviane Philipps, Benoit Liquet: Estimation of extended mixed models using latent classes and latent processes: the R package lcmm (2015) arXiv
  7. Arnošt Komárek; Lenka Komárková: Capabilities of R Package mixAK for Clustering Based on Multivariate Continuous and Discrete Longitudinal Data (2014) not zbMATH
  8. Heinzl, Felix; Tutz, Gerhard: Clustering in linear-mixed models with a group fused lasso penalty (2014)
  9. Rodríguez, Carlos E.; Walker, Stephen G.: Univariate Bayesian nonparametric mixture modeling with unimodal kernels (2014)
  10. Komárek, Arnošt; Komárková, Lenka: Clustering for multivariate continuous and discrete longitudinal data (2013)
  11. Cabral, Celso Rômulo Barbosa; Lachos, Víctor Hugo; Madruga, Maria Regina: Bayesian analysis of skew-normal independent linear mixed models with heterogeneity in the random-effects population (2012)
  12. Komárek, Arnošt: A new R package for Bayesian estimation of multivariate normal mixtures allowing for selection of the number of components and interval-censored data (2009)