106
Views
0
CrossRef citations to date
0
Altmetric
Research Article

Kernel density estimation by genetic algorithm

ORCID Icon
Pages 1263-1281 | Received 08 Mar 2022, Accepted 06 Oct 2022, Published online: 14 Nov 2022

References

  • Girolami M, He C. Probability density estimation from optimally condensed data samples. IEEE Trans Pattern Anal Mach Intell. 2003;25(10):1253–1264.
  • He C, Girolami M. Novelty detection employing an L2 optimal non-parametric density estimator. Pattern Recognit Lett. 2004;25(12):1389–1397.
  • Nishida K, Naito K. Kernel density estimation by stagewise algorithm with a simple dictionary. arXiv:2107.13430, Cornell university, 2021.
  • Klemelä J. Density estimation with stagewise optimization of the empirical risk. Mach Learn. 2007;67(3):169–195.
  • Naito K, Eguchi S. Density estimation with minimization of U-divergence. Mach Learn. 2013;90(1):29–57.
  • Bregman LM. The relaxation method of finding the common point of convex sets and its application to the solution of problems in convex programming. USSR Comput Math Math Phys. 1967;7(3):200–217.
  • Zhang C, Jiang Y, Chai Y. Penalized bregman divergence for large-dimensional regression and classification. Biometrika. 2010;97(3):551–566.
  • Zhang C, Jiang Y, Shang Z. New aspects of bregman divergence in regression and classification with parametric and nonparametric estimation. Canadian J Statist. 2009;37(1):119–139.
  • Forrest S. Genetic algorithms: principles of natural selection applied to computation. Science. 1993;261(5123):872–878.
  • Goldberg DE, Holland JH. Genetic algorithms and machine learning. Mach Learn. 1988;3:95–99.
  • Haupt RL, Haupt SE. Practical genetic algorithms. 2nd ed. Hoboken (NJ): Wiley-Interscience; 2004.
  • Holland JH. Genetic algorithms. Sci Am. 1992;267(1):66–72.
  • Sivanandam SN, Deepa SN. Introduction to genetic algorithms. Berlin: Springer; 2008.
  • Duczmal L, Cancado ALF, Takahashi RHC, et al. A genetic algorithm for irregularly shaped spatial scan statistics. Comput Stat Data Anal. 2007;52(1):43–52.
  • Koukouvinos C, Mylona K, Simos DE. Exploring k-circulant supersaturated designs via genetic algorithms. Comput Stat Data Anal. 2007;51(6):2958–2968.
  • Vovan T, Phamtoan D, Tranthituy D. Automatic genetic algorithm in clustering for discrete elements. Commun Statist Simul Comput. 2021;50(6):1679–1694.
  • Brito J, Fadel A, Semaan G. A genetic algorithm applied to optimal allocation in stratified sampling. Commun Statist – Simul Comput. 2022;51(7):3714–3732.
  • Goldberg DE. Genetic algorithms in search, optimization, and machine learning. Boston (MA): Addison-Wesley; 1989.
  • Bowman A. An alternative method of cross-validation for the smoothing of density estimates. Biometrika. 1984;71(2):353–360.
  • Rudemo M. Empirical choice of histograms and kernel density estimators. Scandinavian J Statist. 1982;9:65–78.
  • Duong T, Hazelton ML. Plug-in bandwidth matrices for bivariate kernel density estimation. J Nonparametr Stat. 2003;15(1):17–30.
  • Wand MP, Jones MC. Comparison of smoothing parametrizations in bivariate kernel density estimation. J Am Stat Assoc. 1993;88(422):520–528.
  • Nash WJ, Sellers TL, Talbot SR, et al. The population biology of abalone (haliotis species) in Tasmania. I. Blacklip abalone (H. Rubra) from the north coast and islands of bass strait, sea fisheries division. Technical Report No. 48 (ISSN 1034–3288), 1994.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.