sm

R package sm: Smoothing methods for nonparametric regression and density estimation. This is software linked to the book ’Applied Smoothing Techniques for Data Analysis - The Kernel Approach with S-Plus Illustrations’ Oxford University Press.

Keywords for this software

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References in zbMATH (referenced in 70 articles , 1 standard article )

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  1. Arsalane Chouaib Guidoum: Kernel Estimator and Bandwidth Selection for Density and its Derivatives: The kedd Package (2020) arXiv
  2. Lisa Amrhein, Christiane Fuchs: stochprofML: Stochastic Profiling Using Maximum Likelihood Estimation in R (2020) arXiv
  3. Giorgio Speranza, Roberto Canteri: RxpsG a new open project for Photoelectron and Electron Spectroscopy data processing (2019) not zbMATH
  4. Rivas-Martínez, G. I.; Jiménez-Gamero, M. D.; Moreno-Rebollo, J. L.: A two-sample test for the error distribution in nonparametric regression based on the characteristic function (2019)
  5. Nott, David J.; Drovandi, Christopher C.; Mengersen, Kerrie; Evans, Michael: Approximation of Bayesian predictive (p)-values with regression ABC (2018)
  6. Salehi, Mahdi; Azzalini, Adelchi: On application of the univariate Kotz distribution and some of its extensions (2018)
  7. Zhang, Xin; Wang, Chong; Wu, Yichao: Functional envelope for model-free sufficient dimension reduction (2018)
  8. Adriano Zambom and Michael Akritas: NonpModelCheck: An R Package for Nonparametric Lack-of-Fit Testing and Variable Selection (2017) not zbMATH
  9. Eichner, Gerrit: Kader -- an R package for nonparametric kernel adjusted density estimation and regression (2017)
  10. Li, Dewang: Kernel estimations for multivariate density functional with bootstrap (2017)
  11. Liu, Chong; Ray, Surajit; Hooker, Giles: Functional principal component analysis of spatially correlated data (2017)
  12. Reyes, Miguel; Francisco-Fernández, Mario; Cao, Ricardo: Bandwidth selection in kernel density estimation for interval-grouped data (2017)
  13. Teixeira, Francisco Curado; Quintas, João; Maurya, Pramod; Pascoal, António: Robust particle filter formulations with application to terrain-aided navigation (2017)
  14. Bagnato, L.; De Capitani, L.; Punzo, A.: The Kullback-Leibler autodependogram (2016)
  15. García-Portugués, Eduardo; Van Keilegom, Ingrid; Crujeiras, Rosa M.; González-Manteiga, Wenceslao: Testing parametric models in linear-directional regression (2016)
  16. González, M.; Minuesa, C.; del Puerto, I.: Maximum likelihood estimation and expectation-maximization algorithm for controlled branching processes (2016)
  17. Weller, Zachary D.; Hoeting, Jennifer A.: A review of nonparametric hypothesis tests of isotropy properties in spatial data (2016)
  18. Luca Bagnato, Lucio De Capitani, Angelo Mazza, Antonio Punzo: SDD: An R Package for Serial Dependence Diagrams (2015) not zbMATH
  19. Berentsen, Geir Drage; Tjøstheim, Dag: Recognizing and visualizing departures from independence in bivariate data using local Gaussian correlation (2014)
  20. Menardi, Giovanna; Torelli, Nicola: Training and assessing classification rules with imbalanced data (2014)

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