R

R is a language and environment for statistical computing and graphics. It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories (formerly AT&T, now Lucent Technologies) by John Chambers and colleagues. R can be considered as a different implementation of S. There are some important differences, but much code written for S runs unaltered under R. R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, ...) and graphical techniques, and is highly extensible. The S language is often the vehicle of choice for research in statistical methodology, and R provides an Open Source route to participation in that activity. One of R’s strengths is the ease with which well-designed publication-quality plots can be produced, including mathematical symbols and formulae where needed. Great care has been taken over the defaults for the minor design choices in graphics, but the user retains full control. R is the base for many R packages listed in https://cran.r-project.org/

This software is also referenced in ORMS.


References in zbMATH (referenced in 8601 articles , 6 standard articles )

Showing results 1 to 20 of 8601.
Sorted by year (citations)

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  1. Abdi, Hervé; Beaton, Derek: Principal component and correspondence analyses using R (to appear) (2021)
  2. Alex Stringer: Implementing Adaptive Quadrature for Bayesian Inference: the aghq Package (2021) arXiv
  3. Andrea Bommert, Michel Lang: stabm: Stability Measures for Feature Selection (2021) not zbMATH
  4. Andreas Hill, Alexander Massey, Daniel Mandallaz: The R Package forestinventory: Design-Based Global and Small Area Estimations for Multiphase Forest Inventories (2021) not zbMATH
  5. Arnald Puy, Samuele Lo Piano, Andrea Saltelli, Simon A. Levin: sensobol: an R package to compute variance-based sensitivity indices (2021) arXiv
  6. Artur Karczmarczyk, Jarosław Jankowski, Jarosław Wątróbski: OONIS - Object-Oriented Network Infection Simulator (2021) not zbMATH
  7. Bakar, S. A. Abu; Nadarajah, S.: Composite models with underlying folded distributions (2021)
  8. Baltagi, Badi H.: Econometric analysis of panel data (2021)
  9. Baumer, Benjamin S.; Kaplan, Daniel T.; Horton, Nicholas J.: Modern data science with R (to appear) (2021)
  10. Benjamin F. Maier: epipack: An infectious disease modeling package for Python (2021) not zbMATH
  11. Bhattacharjee, Atanu: Bayesian approaches in oncology using R and OpenBUGS (2021)
  12. Brinnae Bent, Maria Henriquez, Jessilyn Dunn: cgmquantify: Python and R packages for comprehensive analysis of interstitial glucose and glycemic variability from continuous glucose monitor data (2021) arXiv
  13. Cai, Yongli; Zhao, Shi; Niu, Yun; Peng, Zhihang; Wang, Kai; He, Daihai; Wang, Weiming: Modelling the effects of the contaminated environments on tuberculosis in Jiangsu, China (2021)
  14. Carstensen, Bendix: Epidemiology with R (2021)
  15. Chambers, Donald R.; Lu, Qin: Introduction to financial mathematics. With computer applications (to appear) (2021)
  16. Claudio Zandonella Callegher, Giulia Bertoldo, Enrico Toffalini, Anna Vesely, Angela Andreella, Massimiliano Pastore, Gianmarco Altoè: PRDA: An R package for Prospective and Retrospective Design Analysis (2021) not zbMATH
  17. Cochrane, Courtney; Ba, Demba; Klerman, Elizabeth B.; St. Hilaire, Melissa A.: An ensemble mixed effects model of sleep loss and performance (2021)
  18. David Issa Mattos, Érika Martins Silva Ramos: Bayesian Paired-Comparison with the bpcs Package (2021) arXiv
  19. Debashis Chatterjee: Novel Bayesian Procrustes Variance based Inferences in Geometric Morphometrics and Novel R package: BPviGM1 (2021) arXiv
  20. Efron, Bradley; Hastie, Trevor: Computer age statistical inference. Algorithms, evidence, and data science (to appear) (2021)

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