References in zbMATH (referenced in 14 articles )

Showing results 1 to 14 of 14.
Sorted by year (citations)

  1. Hušková, Marie; Meintanis, Simos G.; Pretorius, Charl: Tests for validity of the semiparametric heteroskedastic transformation model (2020)
  2. Liu, Yu; De Brabanter, Kris: Smoothed nonparametric derivative estimation using weighted difference quotients (2020)
  3. Xie, Fangzheng; Xu, Yanxun: Adaptive Bayesian nonparametric regression using a kernel mixture of polynomials with application to partial linear models (2020)
  4. Cheng, Gang; Chen, Yen-Chi: Nonparametric inference via bootstrapping the debiased estimator (2019)
  5. Górecki, Tomasz; Smaga, Łukasz: fdANOVA: an R software package for analysis of variance for univariate and multivariate functional data (2019)
  6. Nagy, Stanislav; Ferraty, Frédéric: Data depth for measurable noisy random functions (2019)
  7. Sebastian Calonico; Matias Cattaneo; Max Farrell: nprobust: Nonparametric Kernel-Based Estimation and Robust Bias-Corrected Inference (2019) not zbMATH
  8. Wang, WenWu; Yu, Ping; Lin, Lu; Tong, Tiejun: Robust estimation of derivatives using locally weighted least absolute deviation regression (2019)
  9. Adriano Zambom and Michael Akritas: NonpModelCheck: An R Package for Nonparametric Lack-of-Fit Testing and Variable Selection (2017) not zbMATH
  10. Gijbels, Irène; Omelka, Marek; Veraverbeke, Noël: Partial and average copulas and association measures (2015)
  11. Gijbels, Irène; Omelka, Marek; Veraverbeke, Noël: Estimation of a copula when a covariate affects only marginal distributions (2015)
  12. Wang, Wenwu; Lin, Lu: Derivative estimation based on difference sequence via locally weighted least squares regression (2015)
  13. Pablo Montero; José Vilar: TSclust: An R Package for Time Series Clustering (2014) not zbMATH
  14. De Brabanter, Kris; De Brabanter, Jos; De Moor, Bart; Gijbels, Irène: Derivative estimation with local polynomial fitting (2013)