An R Package of Minorization-Maximization Algorithm via the Assembly--Decomposition Technology R package MMAD version 2.0.1 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). Software Depends: R (>= 2.10) Imports: utils Suggests: testthat (>= 3.0.0) Jiaqi Gu <jiaqigu@usf.edu> Comprehensive R Archive Network (CRAN) Xifen Huang [aut], Jinfeng Xu [aut], Jiaqi Gu [aut, cre] GPL-3 2026-03-12 application/tgz https://CRAN.R-project.org/package=MMAD doi:10.32614/CRAN.package.MMAD