Clustering Data with Non-Ignorable Missingness using Semi-Parametric Mixture Models

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) .


News

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("MNARclust")

1.0.0 by Matthieu Marbac, 2 months ago


https://arxiv.org/abs/2009.07662


Browse source code at https://github.com/cran/MNARclust


Authors: Marie Du Roy de Chaumaray [aut] , Matthieu Marbac [aut, cre, cph]


Documentation:   PDF Manual  


GPL (>= 2) license


Imports Rcpp, parallel, sn, rmutil

Linking to Rcpp, RcppArmadillo


See at CRAN