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Genetic algorithms and their statistical applications: an introduction

Citations

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Cited by:

  1. Swait, Joffre, 2023. "Distribution-free estimation of individual parameter logit (IPL) models using combined evolutionary and optimization algorithms," Journal of choice modelling, Elsevier, vol. 47(C).
  2. Winker, Peter & Gilli, Manfred, 2004. "Applications of optimization heuristics to estimation and modelling problems," Computational Statistics & Data Analysis, Elsevier, vol. 47(2), pages 211-223, September.
  3. Ambrogi, Federico & Lama, Nicola & Boracchi, Patrizia & Biganzoli, Elia, 2007. "Selection of artificial neural network models for survival analysis with Genetic Algorithms," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 30-42, September.
  4. Richard A. Davis & Thomas C. M. Lee & Gabriel A. Rodriguez‐Yam, 2008. "Break Detection for a Class of Nonlinear Time Series Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(5), pages 834-867, September.
  5. Francesco Battaglia, 2001. "Genetic alghorithms, pseudo-random number generators, and Markov chain Monte Carlo methods," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(1-2), pages 129-154.
  6. Francesco Battaglia & Mattheos K. Protopapas, 2010. "Multi-regime models for nonlinear nonstationary time series," Working Papers 026, COMISEF.
  7. Firat, Aykut & Chatterjee, Sangit & Yilmaz, Mustafa, 2007. "Genetic clustering of social networks using random walks," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 6285-6294, August.
  8. Giulia Vannucci & Anna Gottard, 2023. "An evolutionary estimation procedure for generalized semilinear regression trees," Computational Statistics, Springer, vol. 38(4), pages 1927-1946, December.
  9. Francesco Battaglia & Mattheos Protopapas, 2012. "Multi–regime models for nonlinear nonstationary time series," Computational Statistics, Springer, vol. 27(2), pages 319-341, June.
  10. Abdulrashid Muhammad Kabir & Mohsin Kamal & Fiaz Ahmad & Zahid Ullah & Fahad R. Albogamy & Ghulam Hafeez & Faizan Mehmood, 2021. "Optimized Economic Load Dispatch with Multiple Fuels and Valve-Point Effects Using Hybrid Genetic–Artificial Fish Swarm Algorithm," Sustainability, MDPI, vol. 13(19), pages 1-27, September.
  11. Baragona, Roberto & Battaglia, Francesco & Calzini, Claudio, 2001. "Genetic algorithms for the identification of additive and innovation outliers in time series," Computational Statistics & Data Analysis, Elsevier, vol. 37(1), pages 1-12, July.
  12. Chun-Xia Zhang & Guan-Wei Wang & Jun-Min Liu, 2015. "RandGA: injecting randomness into parallel genetic algorithm for variable selection," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(3), pages 630-647, March.
  13. Wang, Zhenzhong & Zhu, Zhengyuan & Yu, Cindy, 2025. "Variable Selection in Macroeconomic Forecasting with Many Predictors," Econometrics and Statistics, Elsevier, vol. 36(C), pages 19-36.
  14. Gabriele Perrone & Gabriele Soffritti, 2024. "Parsimonious Seemingly Unrelated Contaminated Normal Cluster-Weighted Models," Journal of Classification, Springer;The Classification Society, vol. 41(3), pages 533-567, November.
  15. Roberto Baragona & Francesco Battaglia & Domenico Cucina, 2004. "Estimating threshold subset autoregressive moving-average models by genetic algorithms," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(1), pages 39-61.
  16. Fouskakis, D., 2012. "Bayesian variable selection in generalized linear models using a combination of stochastic optimization methods," European Journal of Operational Research, Elsevier, vol. 220(2), pages 414-422.
  17. Francesco Battaglia & Mattheos Protopapas, 2012. "An analysis of global warming in the Alpine region based on nonlinear nonstationary time series models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 21(3), pages 315-334, August.
  18. Chun-Xia Zhang & Jiang-She Zhang & Sang-Woon Kim, 2016. "PBoostGA: pseudo-boosting genetic algorithm for variable ranking and selection," Computational Statistics, Springer, vol. 31(4), pages 1237-1262, December.
  19. Zhenzhong Wang & Zhengyuan Zhu & Cindy Yu, 2020. "Variable Selection in Macroeconomic Forecasting with Many Predictors," Papers 2007.10160, arXiv.org.
  20. Gray, J. Brian & Fan, Guangzhe, 2008. "Classification tree analysis using TARGET," Computational Statistics & Data Analysis, Elsevier, vol. 52(3), pages 1362-1372, January.
  21. Baragona, R. & Battaglia, F. & Cucina, D., 2004. "Fitting piecewise linear threshold autoregressive models by means of genetic algorithms," Computational Statistics & Data Analysis, Elsevier, vol. 47(2), pages 277-295, September.
  22. Roverato, Alberto & Paterlini, Sandra, 2004. "Technological modelling for graphical models: an approach based on genetic algorithms," Computational Statistics & Data Analysis, Elsevier, vol. 47(2), pages 323-337, September.
  23. Jianxin Yang & Jian Gong & Wenwu Tang & Yang Shen & Chunyan Liu & Jing Gao, 2019. "Delineation of Urban Growth Boundaries Using a Patch-Based Cellular Automata Model under Multiple Spatial and Socio-Economic Scenarios," Sustainability, MDPI, vol. 11(21), pages 1-27, November.
  24. Francesco Battaglia & Mattheos K. Protopapas, 2011. "Time‐varying multi‐regime models fitting by genetic algorithms," Journal of Time Series Analysis, Wiley Blackwell, vol. 32(3), pages 237-252, May.
  25. Reynès, Christelle & Sabatier, Robert & Molinari, Nicolas & Lehmann, Sylvain, 2008. "A new genetic algorithm in proteomics: Feature selection for SELDI-TOF data," Computational Statistics & Data Analysis, Elsevier, vol. 52(9), pages 4380-4394, May.
  26. Pattarin, Francesco & Paterlini, Sandra & Minerva, Tommaso, 2004. "Clustering financial time series: an application to mutual funds style analysis," Computational Statistics & Data Analysis, Elsevier, vol. 47(2), pages 353-372, September.
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