ggplot2

R package ggplot2: An implementation of the Grammar of Graphics , An implementation of the grammar of graphics in R. It combines the advantages of both base and lattice graphics: conditioning and shared axes are handled automatically, and you can still build up a plot step by step from multiple data sources. It also implements a sophisticated multidimensional conditioning system and a consistent interface to map data to aesthetic attributes. See the ggplot2 website for more information, documentation and examples. (Source: http://cran.r-project.org/web/packages)


References in zbMATH (referenced in 109 articles , 2 standard articles )

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  1. Alicja Gosiewska; Przemyslaw Biecek: auditor: an R Package for Model-Agnostic Visual Validation and Diagnostic (2018) arXiv
  2. Borcard, Daniel; Gillet, François; Legendre, Pierre: Numerical ecology with R (2018)
  3. Chen, L.; Davydov, Y.; Gribkova, N.; Zitikis, R.: Estimating the index of increase via balancing deterministic and random data (2018)
  4. Diane Uschner; David Schindler; Ralf-Dieter Hilgers; Nicole Heussen: randomizeR: An R Package for the Assessment and Implementation of Randomization in Clinical Trials (2018)
  5. D’Urso, Pierpaolo; De Giovanni, Livia; Massari, Riccardo: Robust fuzzy clustering of multivariate time trajectories (2018)
  6. Eun-Kyung Lee: PPtreeViz: An R Package for Visualizing Projection Pursuit Classification Trees (2018)
  7. Garth Tarr; Samuel Müller; Alan Welsh: mplot: An R Package for Graphical Model Stability and Variable Selection Procedures (2018)
  8. Georgios Papageorgiou: BNSP: an R Package for Fitting Bayesian Regression Models With Semiparametric Mean and Variance Functions (2018) arXiv
  9. Martijn Tennekes: tmap: Thematic Maps in R (2018)
  10. Mathieu Carmassi; Pierre Barbillon; Matthieu Chiodetti; Merlin Keller; Eric Parent: CaliCo: a R package for Bayesian calibration (2018) arXiv
  11. Natalia da Silva, Eun-Kyung Lee, Di Cook: A Projection Pursuit Forest Algorithm for Supervised Classification (2018) arXiv
  12. Xia, Yinglin; Sun, Jun; Chen, Ding-Geng: Statistical analysis of microbiome data with R (2018)
  13. Alexandra Kuznetsova; Per Brockhoff; Rune Christensen: lmerTest Package: Tests in Linear Mixed Effects Models (2017)
  14. Antoine Filipovic-Pierucci, Kevin Zarca, Isabelle Durand-Zaleski: Markov Models for Health Economic Evaluations: The R Package heemod (2017) arXiv
  15. Baumer, Benjamin S.; Kaplan, Daniel T.; Horton, Nicholas J.: Modern data science with R (2017)
  16. Beckerman, Andrew P.; Petchey, Owen L.: Getting started with R. An introduction for biologists. (2017)
  17. Benjamin R. Fitzpatrick, Kerrie Mengersen: A network flow approach to visualising the roles of covariates in random forests (2017) arXiv
  18. Bezanson, Jeff; Edelman, Alan; Karpinski, Stefan; Shah, Viral B.: Julia: a fresh approach to numerical computing (2017)
  19. Bodenham, Dean A.; Adams, Niall M.: Continuous monitoring for changepoints in data streams using adaptive estimation (2017)
  20. Bücher, Axel; Kinsvater, Paul; Kojadinovic, Ivan: Detecting breaks in the dependence of multivariate extreme-value distributions (2017)

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