roptim - General Purpose Optimization in R using C++
Perform general purpose optimization in R using C++. A unified wrapper interface is provided to call C functions of the five optimization algorithms ('Nelder-Mead', 'BFGS', 'CG', 'L-BFGS-B' and 'SANN') underlying optim().
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armadillobfgsconjugate-gradientl-bfgs-bnelder-meadoptimrcppsimulated-annealingopenblascpp
7.85 score 22 stars 28 dependents 15 scripts 2.5k downloadsjmcm - Joint Mean-Covariance Models using 'Armadillo' and S4
Fit joint mean-covariance models for longitudinal data. The models and their components are represented using S4 classes and methods. The core computational algorithms are implemented using the 'Armadillo' C++ library for numerical linear algebra and 'RcppArmadillo' glue.
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cholesky-decompositioncovariance-modelsopenblascppopenmp
5.18 score 5 stars 1 dependents 10 scripts 227 downloadsrminqa - Derivative-Free Optimization in R using C++
Perform derivative-free optimization algorithms in R using C++. A wrapper interface is provided to call C function of the 'bobyqa' implementation (See <https://github.com/emmt/Algorithms/tree/master/bobyqa>).
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cpp
3.18 score 1 dependents 528 downloads