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References in zbMATH (referenced in 408 articles )

Showing results 41 to 60 of 408.
Sorted by year (citations)

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  1. García, Oscar: Estimating reducible stochastic differential equations by conversion to a least-squares problem (2019)
  2. Guerra, Maria Letizia; Sorini, Laerte; Stefanini, Luciano: Quantile and expectile smoothing based on (L_1)-norm and (L_2)-norm fuzzy transforms (2019)
  3. Gu, Mengyang: Jointly robust prior for Gaussian stochastic process in emulation, calibration and variable selection (2019)
  4. Hadrien Lorenzo, Jérôme Saracco, Rodolphe Thiébaut: Supervised Learning for Multi-Block Incomplete Data (2019) arXiv
  5. Hay-Jahans, Christopher: R companion to elementary applied statistics (2019)
  6. Hyeyoung Maeng, Piotr Fryzlewicz: Detecting linear trend changes and point anomalies in data sequences (2019) arXiv
  7. Ickowicz, Adrien; Ford, Jessica; Hayes, Keith: A mixture model approach for compositional data: inferring land-use influence on point-referenced water quality measurements (2019)
  8. Jaeger, Byron C.; Long, D. Leann; Long, Dustin M.; Sims, Mario; Szychowski, Jeff M.; Min, Yuan-I; McClure, Leslie A.; Howard, George; Simon, Noah: Oblique random survival forests (2019)
  9. João Duarte; Vinícius Mayrink: slfm: An R Package to Evaluate Coherent Patterns in Microarray Data via Factor Analysis (2019) not zbMATH
  10. Karmakar, B.; French, B.; Small, D. S.: Integrating the evidence from evidence factors in observational studies (2019)
  11. Kaul, Abhishek; Jandhyala, Venkata K.; Fotopoulos, Stergios B.: An efficient two step algorithm for high dimensional change point regression models without grid search (2019)
  12. Li, Gang; Wang, Xiaoyan: Prediction accuracy measures for a nonlinear model and for right-censored time-to-event data (2019)
  13. Lindsay Rutter, Susan VanderPlas, Dianne Cook, Michelle A. Graham: ggenealogy: An R Package for Visualizing Genealogical Data (2019) not zbMATH
  14. Lund, Adam; Hansen, Niels Richard: Sparse network estimation for dynamical spatio-temporal array models (2019)
  15. Macdonald, Benn; Husmeier, Dirk: Model selection via marginal likelihood estimation by combining thermodynamic integration and gradient matching (2019)
  16. Mai, Qing; Yang, Yi; Zou, Hui: Multiclass sparse discriminant analysis (2019)
  17. Mathieu Fauvernier; Laurent Remontet; Zoé Uhry; Nadine Bossard; Laurent Roche: survPen: an R package for hazard and excess hazard modelling with multidimensional penalized splines (2019) not zbMATH
  18. Michael Messer: Bivariate change point detection: joint detection of changes in expectation and variance (2019) arXiv
  19. Michel Lang, Martin Binder, Jakob Richter, Patrick Schratz, Florian Pfisterer, Stefan Coors, Quay Au, Giuseppe Casalicchio, Lars Kotthoff, Bernd Bischl: mlr3: A modern object-oriented machine learning framework in R (2019) not zbMATH
  20. Mihai Tivadar: OasisR: An R Package to Bring Some Order to the World of Segregation Measurement (2019) not zbMATH

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Further publications can be found at: http://journal.r-project.org/