References in zbMATH (referenced in 13 articles , 1 standard article )

Showing results 1 to 13 of 13.
Sorted by year (citations)

  1. Biernacki, Christophe; Marbac, Matthieu; Vandewalle, Vincent: Gaussian-based visualization of Gaussian and non-Gaussian-based clustering (2021)
  2. Corneli, Marco; Bouveyron, Charles; Latouche, Pierre: Co-clustering of ordinal data via latent continuous random variables and not missing at random entries (2020)
  3. Giordani, Paolo; Ferraro, Maria Brigida; Martella, Francesca: An introduction to clustering with R (2020)
  4. Murphy, Keefe; Murphy, Thomas Brendan: Gaussian parsimonious clustering models with covariates and a noise component (2020)
  5. Selosse, Margot; Jacques, Julien; Biernacki, Christophe: Model-based co-clustering for mixed type data (2020)
  6. Amiri, Leila; Khazaei, Mojtaba; Ganjali, Mojtaba: Mixtures of general location model with factor analyzer covariance structure for clustering mixed type data (2019)
  7. Biernacki, Christophe; Lourme, Alexandre: Unifying data units and models in (co-)clustering (2019)
  8. Fernández, Daniel; Arnold, Richard; Pledger, Shirley; Liu, Ivy; Costilla, Roy: Finite mixture biclustering of discrete type multivariate data (2019)
  9. Alexander Foss; Marianthi Markatou: kamila: Clustering Mixed-Type Data in R and Hadoop (2018) not zbMATH
  10. Fop, Michael; Murphy, Thomas Brendan: Variable selection methods for model-based clustering (2018)
  11. O’Hagan, Adrian; Ferrari, Colm: Model-based and nonparametric approaches to clustering for data compression in actuarial applications (2017)
  12. Tekumalla, Lavanya Sita; Rajan, Vaibhav; Bhattacharyya, Chiranjib: Vine copulas for mixed data: multi-view clustering for mixed data beyond meta-Gaussian dependencies (2017)
  13. McParland, Damien; Gormley, Isobel Claire: Model based clustering for mixed data: clustMD (2016)