Clustering of data under a non-ignorable missingness mechanism. Clustering is achieved by a semi-parametric mixture model and missingness is managed by using the pattern-mixture approach. More details of the approach are available in Du Roy de Chaumaray et al. (2020) <arXiv:2009.07662>.
| Version: | 1.1.0 |
| Depends: | R (≥ 3.5) |
| Imports: | Rcpp, parallel, sn, rmutil |
| LinkingTo: | Rcpp, RcppArmadillo |
| Published: | 2021-12-02 |
| Author: | Marie Du Roy de Chaumaray [aut], Matthieu Marbac [aut, cre, cph] |
| Maintainer: | Matthieu Marbac <matthieu.marbac-lourdelle at ensai.fr> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: | https://arxiv.org/abs/2009.07662 |
| NeedsCompilation: | yes |
| CRAN checks: | MNARclust results |
| Reference manual: | MNARclust.pdf |
| Package source: | MNARclust_1.1.0.tar.gz |
| Windows binaries: | r-devel: MNARclust_1.1.0.zip, r-release: MNARclust_1.1.0.zip, r-oldrel: MNARclust_1.1.0.zip |
| macOS binaries: | r-release (arm64): MNARclust_1.1.0.tgz, r-oldrel (arm64): MNARclust_1.1.0.tgz, r-release (x86_64): MNARclust_1.1.0.tgz, r-oldrel (x86_64): MNARclust_1.1.0.tgz |
| Old sources: | MNARclust archive |
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