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 190 articles , 2 standard articles )

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  1. RESSTE Network; et al.: Analyzing spatio-temporal data with R: everything you always wanted to know -- but were afraid to ask (2017)
  2. Robert Pearce and R. Setzer and Cory Strope and Nisha Sipes and John Wambaugh: httk: R Package for High-Throughput Toxicokinetics (2017) not zbMATH
  3. Samuel Lendle; Joshua Schwab; Maya Petersen; Mark van der Laan: ltmle: An R Package Implementing Targeted Minimum Loss-Based Estimation for Longitudinal Data (2017) not zbMATH
  4. Schaarschmidt, Frank: Multiple treatment comparisons in analysis of covariance with interaction, SCI for treatment covariate interaction (2017)
  5. Starunova, Olga A.; Rudnev, Sergey G.; Starodubov, Vladimir I.: HCViewer: software and technology for quality control and processing raw mass data of preventive screening (2017)
  6. Tan, Teck Kiang: Doubly classified model with R (2017)
  7. Templ, Matthias: Statistical disclosure control for microdata. Methods and applications in R (2017)
  8. Tomokazu Fujino: vdmR: Generating Web-Based Visual Data Mining Tools with R (2017) not zbMATH
  9. Tyralis, Hristos; Papacharalampous, Georgia: Variable selection in time series forecasting using random forests (2017)
  10. Wilcox, Rand: Modern statistics for the social and behavioral sciences. A practical introduction (2017)
  11. Xu, Zheng: Book review of: A. Hector, The new statistics with R. An introduction for biologists (2017)
  12. Angelopoulos, Nicos; Abdallah, Samer; Giamas, Georgios: Advances in integrative statistics for logic programming (2016)
  13. 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)
  14. Bodenham, Dean A.; Adams, Niall M.: A comparison of efficient approximations for a weighted sum of chi-squared random variables (2016)
  15. Ekstrøm, Claus Thorn: The R primer (2016)
  16. Faraway, Julian J.: Extending the linear model with R. Generalized linear, mixed effects and nonparametric regression models. (2016)
  17. Gillespie, Colin S.; Golightly, Andrew: Diagnostics for assessing the linear noise and moment closure approximations (2016)
  18. Krause, Andreas: Book review of: A. Unwin, Graphical data analysis with R. (2016)
  19. Kurtoğlu, Fikriye; Revan Özkale, M.: Liu estimation in generalized linear models: application on gamma distributed response variable (2016)
  20. Marius Hofert; Martin Mächler: Parallel and Other Simulations in R Made Easy: An End-to-End Study (2016) not zbMATH