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:

References in zbMATH (referenced in 28 articles )

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  1. Beams, Alexander B.; Toth, Damon J.A.; Khader, Karim; Adler, Frederick R.: Harnessing intra-host strain competition to limit antibiotic resistance: mathematical model results (2016)
  2. Bodenham, Dean A.; Adams, Niall M.: A comparison of efficient approximations for a weighted sum of chi-squared random variables (2016)
  3. Kurtoğlu, Fikriye; Revan Özkale, M.: Liu estimation in generalized linear models: application on gamma distributed response variable (2016)
  4. Bruzzese, Dario; Vistocco, Domenico: DESPOTA: dendrogram slicing through a pemutation test approach (2015)
  5. D’Enza, Alfonso Iodice; Markos, Angelos: Low-dimensional tracking of association structures in categorical data (2015)
  6. Faraway, Julian J.: Linear models with R (2015)
  7. Heiberger, Richard M.; Holland, Burt: Statistical analysis and data display. An intermediate course with examples in R (2015)
  8. Roy Chowdhury, Niladri; Cook, Dianne; Hofmann, Heike; Majumder, Mahbubul; Lee, Eun-Kyung; Toth, Amy L.: Using visual statistical inference to better understand random class separations in high dimension, low sample size data (2015)
  9. Scholten, Lisa; Schuwirth, Nele; Reichert, Peter; Lienert, Judit: Tackling uncertainty in multi-criteria decision analysis -- an application to water supply infrastructure planning (2015)
  10. Unwin, Antony: Graphical data analysis with R (2015)
  11. Follett, Lendie; Genschel, Ulrike; Hofmann, Heike: A graphical exploration of the deepwater horizon oil spill (2014)
  12. Güniçen, Canan; İnan, Kemal; Türker, Uraz Cengiz; Yenigün, Hüsnü: The relation between preset distinguishing sequences and synchronizing sequences (2014)
  13. Lamigueiro, Oscar Perpiñán: Displaying time series, spatial, and space-time data with R (2014)
  14. Rao, Marepalli B. (ed.); Rao, C. R. (ed.): Computational statistics with R (2014)
  15. Tran, Tony; Yazdanparast, Aida; Suess, Eric A.: Effect of oil spill on birds: a graphical assay of the deepwater horizon oil spill’s impact on birds (2014)
  16. Verzani, John: Using R for introductory statistics (2014)
  17. Bivand, Roger S.; Pebesma, Edzer J.; Gómez-Rubio, Virgilio: Applied spatial data analysis with R (2013)
  18. Wollschläger, Daniel: R compact. The fast introduction into data analysis (2013)
  19. Zhao, Yanchang: R and data mining. Examples and case studies (2013)
  20. Cano, Emilio L.; Moguerza, Javier M.; Redchuk, Andrés: Six Sigma with R. Statistical engineering for process improvement. (2012)

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