MMAD
An R Package of Minorization-Maximization Algorithm via the Assembly--Decomposition Technology
The minorization-maximization (MM) algorithm is a powerful tool for maximizing nonconcave target function. However, for most existing MM algorithms, the surrogate function in the minorization step is constructed in a case-specific manner and requires manual programming. To address this limitation, we develop the R package MMAD, which systematically integrates the assembly--decomposition technology in the MM framework. This new package provides a comprehensive computational toolkit for one-stop inference of complex target functions, including function construction, evaluation, minorization and optimization via MM algorithm. By representing the target function through a hierarchical composition of assembly functions, we design a hierarchical algorithmic structure that supports both bottom-up operations (construction, evaluation) and top-down operation (minorization).
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
2.0.1 |
rolling linux/jammy R-4.5 | MMAD_2.0.1.tar.gz |
38.8 KiB |
2.0.1 |
rolling linux/noble R-4.5 | MMAD_2.0.1.tar.gz |
38.6 KiB |
2.0.1 |
rolling source/ R- | MMAD_2.0.1.tar.gz |
8.4 KiB |
2.0.1 |
latest linux/jammy R-4.5 | MMAD_2.0.1.tar.gz |
38.8 KiB |
2.0.1 |
latest linux/noble R-4.5 | MMAD_2.0.1.tar.gz |
38.6 KiB |
2.0.1 |
latest source/ R- | MMAD_2.0.1.tar.gz |
8.4 KiB |
2.0.1 |
2026-04-26 source/ R- | MMAD_2.0.1.tar.gz |
8.4 KiB |
2.0.1 |
2026-04-23 source/ R- | MMAD_2.0.1.tar.gz |
8.4 KiB |
2.0.1 |
2026-04-09 windows/windows R-4.5 | MMAD_2.0.1.zip |
41.0 KiB |
1.0.0 |
2025-04-20 source/ R- | MMAD_1.0.0.tar.gz |
36.8 KiB |