References in zbMATH (referenced in 34 articles , 1 standard article )

Showing results 1 to 20 of 34.
Sorted by year (citations)

1 2 next

  1. Borrajo, M. I.; González-Manteiga, W.; Martínez-Miranda, M. D.: Bootstrapping kernel intensity estimation for inhomogeneous point processes with spatial covariates (2020)
  2. Casa, Alessandro; Chacón, José E.; Menardi, Giovanna: Modal clustering asymptotics with applications to bandwidth selection (2020)
  3. Jonas Moss, Martin Tveten: kdensity: An R package for kernel density estimation with parametric starts and asymmetric kernels (2019) not zbMATH
  4. Mickaël Binois and Victor Picheny: GPareto: An R Package for Gaussian-Process-Based Multi-Objective Optimization and Analysis (2019) not zbMATH
  5. Teter, Michael D.; Royset, Johannes O.; Newman, Alexandra M.: Modeling uncertainty of expert elicitation for use in risk-based optimization (2019)
  6. Wang, Wei; Lin, Nan; Tang, Xiang: Robust two-sample test of high-dimensional mean vectors under dependence (2019)
  7. Schellhase, Christian; Spanhel, Fabian: Estimating non-simplified vine copulas using penalized splines (2018)
  8. Yang Hu; Carl Scarrott: evmix: An R package for Extreme Value Mixture Modeling, Threshold Estimation and Boundary Corrected Kernel Density Estimation (2018) not zbMATH
  9. Bee, Marco; Benedetti, Roberto; Espa, Giuseppe: Approximate maximum likelihood estimation of the Bingham distribution (2017)
  10. Bonnéry, Daniel; Breidt, F. Jay; Coquet, François: Kernel estimation for a superpopulation probability density function under informative selection (2017)
  11. Eichner, Gerrit: Kader -- an R package for nonparametric kernel adjusted density estimation and regression (2017)
  12. Gramacki, Artur; Gramacki, Jarosław: FFT-based fast bandwidth selector for multivariate kernel density estimation (2017)
  13. Kraus, Daniel; Czado, Claudia: D-vine copula based quantile regression (2017)
  14. Liu, Yang; Hannig, Jan: Generalized fiducial inference for logistic graded response models (2017)
  15. Mazo, Gildas: A semiparametric and location-shift copula-based mixture model (2017)
  16. Grillenzoni, Carlo: Design of blurring mean-shift algorithms for data classification (2016)
  17. Nagler, Thomas; Czado, Claudia: Evading the curse of dimensionality in nonparametric density estimation with simplified vine copulas (2016)
  18. 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
  19. Sreevani; Murthy, C. A.: On bandwidth selection using minimal spanning tree for kernel density estimation (2016)
  20. Thomas Nagler: kdecopula: An R Package for the Kernel Estimation of Bivariate Copula Densities (2016) arXiv

1 2 next