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CEoptim: Cross-Entropy R Package for Optimization
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DOI：10.18637/jss.v076.i08.png)
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Abstract
En 中文
The cross-entropy (CE) method is a 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.
Keywords:
constrained optimization
continuous optimization
cross-entropy
discrete optimization
Kullback-Leibler divergence
lasso
maximum likelihood
R
regression
Journal
IF:
8.1
Papers:
622
Citations:
4.6W