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MMAD  

MM Algorithm Based on the Assembly-Decomposition Technology
View on CRAN: Click here


Download and install MMAD package within the R console
Install from CRAN:
install.packages("MMAD")

Install from Github:
library("remotes")
install_github("cran/MMAD")

Install by package version:
library("remotes")
install_version("MMAD", "1.0.0")



Attach the package and use:
library("MMAD")
Maintained by
Dengge Liu
[Scholar Profile | Author Map]
First Published: 2023-07-08
Latest Update: 2023-07-08
Description:
The Minorize-Maximization(MM) algorithm based on Assembly-Decomposition(AD) technology can be used for model estimation of parametric models, semi-parametric models and non-parametric models. We selected parametric models including left truncated normal distribution, type I multivariate zero-inflated generalized poisson distribution and multivariate compound zero-inflated generalized poisson distribution; semiparametric models include Cox model and gamma frailty model; nonparametric model is estimated for type II interval-censored data. These general methods are proposed based on the following papers, Tian, Huang and Xu (2019) , Huang, Xu and Tian (2019) , Zhang and Huang (2022) .
How to cite:
Dengge Liu (2023). MMAD: MM Algorithm Based on the Assembly-Decomposition Technology. R package version 1.0.0, https://cran.r-project.org/web/packages/MMAD. Accessed 10 Apr. 2025.
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Complete documentation for MMAD
Functions, R codes and Examples using the MMAD R package
Full MMAD package functions and examples
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