References in zbMATH (referenced in 23 articles )

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  1. Schellhase, Christian; Spanhel, Fabian: Estimating non-simplified vine copulas using penalized splines (2018)
  2. Yang Hu; Carl Scarrott: evmix: An R package for Extreme Value Mixture Modeling, Threshold Estimation and Boundary Corrected Kernel Density Estimation (2018)
  3. Bee, Marco; Benedetti, Roberto; Espa, Giuseppe: Approximate maximum likelihood estimation of the Bingham distribution (2017)
  4. Bonnéry, Daniel; Breidt, F. Jay; Coquet, François: Kernel estimation for a superpopulation probability density function under informative selection (2017)
  5. Eichner, Gerrit: Kader -- an R package for nonparametric kernel adjusted density estimation and regression (2017)
  6. Gramacki, Artur; Gramacki, Jarosław: FFT-based fast bandwidth selector for multivariate kernel density estimation (2017)
  7. Kraus, Daniel; Czado, Claudia: D-vine copula based quantile regression (2017)
  8. Liu, Yang; Hannig, Jan: Generalized fiducial inference for logistic graded response models (2017)
  9. Mazo, Gildas: A semiparametric and location-shift copula-based mixture model (2017)
  10. Grillenzoni, Carlo: Design of blurring mean-shift algorithms for data classification (2016)
  11. Nagler, Thomas; Czado, Claudia: Evading the curse of dimensionality in nonparametric density estimation with simplified vine copulas (2016)
  12. Nuno Fachada, Joao Rodrigues, Vitor V. Lopes, Rui C. Martins, Agostinho C. Rosa: micompr: An R Package for Multivariate Independent Comparison of Observations (2016) arXiv
  13. Sreevani; Murthy, C. A.: On bandwidth selection using minimal spanning tree for kernel density estimation (2016)
  14. Thomas Nagler: kdecopula: An R Package for the Kernel Estimation of Bivariate Copula Densities (2016) arXiv
  15. Binois, Mickaël; Rullière, Didier; Roustant, Olivier: On the estimation of Pareto fronts from the point of view of copula theory (2015)
  16. Wang, Xuxu; Wang, Yong: Nonparametric multivariate density estimation using mixtures (2015)
  17. Battey, Heather; Linton, Oliver: Nonparametric estimation of multivariate elliptic densities via finite mixture sieves (2014)
  18. Bordes, L.; Kojadinovic, I.; Vandekerkhove, P.: Semiparametric estimation of a two-component mixture of linear regressions in which one component is known (2013)
  19. Naito, Kanta; Eguchi, Shinto: Density estimation with minimization of $U$-divergence (2013)
  20. Rubio, F. J.; Johansen, Adam M.: A simple approach to maximum intractable likelihood estimation (2013)

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