DEoptim

DEoptim: An R Package for Global Optimization by Differential Evolution. This article describes the R package DEoptim which implements the differential evolution algorithm for the global optimization of a real-valued function of a real-valued parameter vector. The implementation of differential evolution in DEoptim interfaces with C code for efficiency. The utility of the package is illustrated via case studies in fitting a Parratt model for X-ray reflectometry data and a Markov-Switching Generalized AutoRegressive Conditional Heteroskedasticity (MSGARCH) model for the returns of the Swiss Market Index.


References in zbMATH (referenced in 39 articles , 1 standard article )

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  1. Boudt, Kris; Wan, Chunlin: The effect of velocity sparsity on the performance of cardinality constrained particle swarm optimization (2020)
  2. Blostein, Martin; Miljkovic, Tatjana: On modeling left-truncated loss data using mixtures of distributions (2019)
  3. Castillo-Páez, Sergio; Fernández-Casal, Rubén; García-Soidán, Pilar: A nonparametric bootstrap method for spatial data (2019)
  4. David Ardia; Keven Bluteau; Kris Boudt; Leopoldo Catania; Denis-Alexandre Trottier: Markov-Switching GARCH Models in R: The MSGARCH Package (2019) not zbMATH
  5. David Ardia; Kris Boudt; Leopoldo Catania: Generalized Autoregressive Score Models in R: The GAS Package (2019) not zbMATH
  6. Cano-Berlanga, Sebastián; Giménez-Gómez, José-Manuel: On Chinese stock markets: how have they evolved over time? (2018)
  7. Dünder, Emre; Gümüştekin, Serpil; Murat, Naci; Cengiz, Mehmet Ali: Variable selection in linear regression analysis with alternative Bayesian information criteria using differential evaluation algorithm (2018)
  8. Eckert, Johanna; Gatzert, Nadine: Risk- and value-based management for non-life insurers under solvency constraints (2018)
  9. Levantesi, Susanna; Menzietti, Massimiliano: Natural hedging in long-term care insurance (2018)
  10. Salehi, Mahdi; Azzalini, Adelchi: On application of the univariate Kotz distribution and some of its extensions (2018)
  11. Serrano-Rubio, Juan Pablo; Hernández-Aguirre, Arturo; Herrera-Guzmán, Rafael: An evolutionary algorithm using spherical inversions (2018)
  12. Thongsook, Saranya: Using the GA package in R program and desirability function to develop a multiple response optimization procedure in case of two responses (2018)
  13. Graham, Jason M.; Kao, Albert B.; Wilhelm, Dylana A.; Garnier, Simon: Optimal construction of army ant living bridges (2017)
  14. Miletić, Steven; Turner, Brandon M.; Forstmann, Birte U.; van Maanen, Leendert: Parameter recovery for the leaky competing accumulator model (2017)
  15. Schubert, Anna-Lena; Hagemann, Dirk; Voss, Andreas; Bergmann, Katharina: Evaluating the model fit of diffusion models with the root mean square error of approximation (2017)
  16. Thongsook, Saranya: Using the GA package in R program and desirability function to develop a multiple response optimization procedure in case of two responses (2017)
  17. Christoph Bergmeir and Daniel Molina and José Benítez: Memetic Algorithms with Local Search Chains in R: The Rmalschains Package (2016) not zbMATH
  18. Pablo Villacorta; J. Verdegay: FuzzyStatProb: An R Package for the Estimation of Fuzzy Stationary Probabilities from a Sequence of Observations of an Unknown Markov Chain (2016) not zbMATH
  19. Pekár, Juraj; Čičková, Zuzana; Brezina, Ivan: Portfolio performance measurement using differential evolution (2016)
  20. Gil, Debora; Roche, David; Borràs, Agnés; Giraldo, Jesús: Terminating evolutionary algorithms at their steady state (2015)

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