MixAll: Clustering and Classification using Model-Based Mixture Models
Algorithms and methods for model-based clustering and classification.
It supports various types of data: continuous, categorical and counting
and can handle mixed data of these types. It can fit Gaussian (with diagonal
covariance structure), gamma, categorical and Poisson models. The algorithms
also support missing values. This package can be used as an independent
alternative to the (not free) 'mixtcomp' software available at
<https://massiccc.lille.inria.fr/>.
| Version: |
1.5.1 |
| Depends: |
R (≥ 3.0.2), rtkore (≥ 1.5.0) |
| Imports: |
methods |
| LinkingTo: |
Rcpp (≥ 0.11.0), rtkore (≥ 1.5.0) |
| Published: |
2019-09-12 |
| Author: |
Serge Iovleff [aut, cre],
Parmeet Bathia [ctb] |
| Maintainer: |
Serge Iovleff <Serge.Iovleff at stkpp.org> |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| Copyright: |
inria, University of Lille |
| NeedsCompilation: |
yes |
| SystemRequirements: |
GNU make |
| Materials: |
NEWS |
| In views: |
Cluster |
| CRAN checks: |
MixAll results |
Documentation:
Downloads:
Reverse dependencies:
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