Laurent Berge, Charles Bouveyron and Stephane Girard
Discriminant analysis and data clustering methods for high dimensional data, based on the assumption that high-dimensional data live in different subspaces with low dimensionality proposing a new parametrization of the Gaussian mixture model which combines the ideas of dimension reduction and constraints on the model.

Discriminant analysis and data clustering methods for high
dimensional data, based on the assumption that high-dimensional data live in
different subspaces with low dimensionality proposing a new parametrization of
the Gaussian mixture model which combines the ideas of dimension reduction and
constraints on the model.

Clustering High Dimensional Data with Hidden Markov Model on
Variable Blocks
c(
person("Yevhen", "Tupikov", email = "yzt116@psu.edu", role = c("aut")),
person("Lin", "Lin", email = "llin@psu.edu", role = "aut"),
person("Lixiang", "Zhang", email = "lzz46@psu.edu", role = "aut"),
person("Jia", "Li", email = "jiali@psu.edu", role = c("aut", "cre")))
Clustering of high dimensional data with Hidden Markov Model on Variable Blocks (HMM-VB) fitted via Baum-Welch algorithm. Clustering is performed by the Modal Baum-Welch algorithm (MBW), which finds modes of the density function. Lin Lin and Jia Li (2017) <http://jmlr.org/papers/v18/16-342.html>.
'AllClass.R' 'AllGeneric.R' 'AllMethod.R' 'clustControl.R'
'trainControl.R' 'hmmvbClust.R' 'hmmvbTrain.R'
'vbSearchControl.R' 'package-HDclust.R' 'RcppExports.R'
'sim3.R' 'sim2.R' 'hmmvbBIC.R' 'hmmvbFindModes.R'
'clustModes.R'
Yevhen Tupikov [aut],
Lin Lin [aut],
Lixiang Zhang [aut],
Jia Li [aut, cre]

c(
person("Yevhen", "Tupikov", email = "yzt116@psu.edu", role = c("aut", "cre")),
person("Lin", "Lin", email = "llin@psu.edu", role = "aut"),
person("Jia", "Li", email = "jiali@psu.edu", role = "aut"))
'AllClass.R' 'AllGeneric.R' 'AllMethod.R' 'clustControl.R'
'trainControl.R' 'hmmvbClust.R' 'hmmvbTrain.R'
'vbSearchControl.R' 'package-HDclust.R' 'RcppExports.R'
'sim3.R' 'sim2.R' 'hmmvbBIC.R'
Yevhen Tupikov [aut, cre],
Lin Lin [aut],
Jia Li [aut]