CEoptim: Cross-Entropy R Package for Optimization. The cross-entropy (CE) method is simple and versatile technique for optimization, based on Kullback-Leibler (or cross-entropy) minimization. The method can be applied to a wide range of optimization tasks, including continuous, discrete, mixed and constrained optimization problems. The new package CEoptim provides the R implementation of the CE method for optimization. We describe the general CE methodology for optimization and well as some useful modifications. The usage and efficacy of CEoptim is demonstrated through a variety of optimization examples, including model fitting, combinatorial optimization, and maximum likelihood estimation.
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References in zbMATH (referenced in 2 articles )
Showing results 1 to 2 of 2.
- Thach, Tien T.; Bris, Radim; Volf, Petr; Coolen, Frank P. A.: Non-linear failure rate: a Bayes study using Hamiltonian Monte Carlo simulation (2020)
- Tim Benham, Qibin Duan, Dirk P. Kroese, Benoit Liquet: CEoptim: Cross-Entropy R Package for Optimization (2015) arXiv