Imputation and low-rank estimation with missing non at random data

This repository hosts the code to impute and estimate low-rank matrices containing Missing Not At Random (MNAR) values. Different matrix completion methods are considered, including a model-based estimation strategy by modelling the missing mechanism distribution. More details are given in [1].

Cite

If you use this code in your project, please cite:

[1] Aude Sportisse, Claire Boyer, and Julie Josse.
Imputation and low-rank estimation with missing non at random data.
arXiv preprint arXiv:1812.11409, 2018.

Get the PDF of the paper here.