MMAD: Minorization-Maximization Algorithm via the...
In MMAD: An R Package of Minorization-Maximization Algorithm via the Assembly--Decomposition Technology
MMAD R Documentation
Minorization-Maximization Algorithm via the Assembly–Decomposition Technology
Description
This function allows the user to maximize the target function f(\boldsymbol{\theta}) using MM algorithm with AD technology.
Usage
MMAD(Function_obj, init, tol = 1e-04)
Arguments
Function_obj
An R list depicting the target function.
init
The initial value \boldsymbol{\theta}^{(0)} for iterative optimization.
tol
The tolerance for convergence detection (default: 1\times 10^{-4}).
Value
The maximizer
\widehat{\boldsymbol{\theta}}=\arg\max_{\boldsymbol{\theta} \in\Theta }f(\boldsymbol{\theta}).
MMAD documentation built on March 12, 2026, 5:07 p.m.
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| MMAD | R Documentation |
Minorization-Maximization Algorithm via the Assembly–Decomposition Technology
Description
This function allows the user to maximize the target function f(\boldsymbol{\theta}) using MM algorithm with AD technology.
Usage
MMAD(Function_obj, init, tol = 1e-04)
Arguments
Function_obj |
An R list depicting the target function. |
init |
The initial value |
tol |
The tolerance for convergence detection (default: |
Value
The maximizer
\widehat{\boldsymbol{\theta}}=\arg\max_{\boldsymbol{\theta} \in\Theta }f(\boldsymbol{\theta}).
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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