mpem
Matrix Partial EM for Incomplete Matrix-Normal Data
Fits single-component and finite-mixture Kronecker-structured matrix-normal models and imputes incomplete matrix-variate data using matrix partial expectation-maximization. General MPEM handles arbitrary missingness, while Rect-MPEM exploits rectangular structural missingness. The methods are described in Lu, Andrews and Browne (2026) "An Efficient EM Algorithm for Both Element-Wise and Structural Missingness in Matrix-Variate Normal Mixture Models" <doi:10.48550/arXiv.2609.00616>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.0 |
rolling linux/jammy R-4.5 | mpem_0.1.0.tar.gz |
163.4 KiB |
0.1.0 |
rolling linux/noble R-4.5 | mpem_0.1.0.tar.gz |
166.9 KiB |
0.1.0 |
rolling source/ R- | mpem_0.1.0.tar.gz |
18.9 KiB |
0.1.0 |
latest linux/jammy R-4.5 | mpem_0.1.0.tar.gz |
163.4 KiB |
0.1.0 |
latest linux/noble R-4.5 | mpem_0.1.0.tar.gz |
166.9 KiB |
0.1.0 |
latest source/ R- | mpem_0.1.0.tar.gz |
18.9 KiB |
0.1.0 |
2026-04-23 source/ R- | mpem_0.1.0.tar.gz |
0 B |