Sweave is a tool that allows to embed the R code for complete data analyses in latex documents. The purpose is to create dynamic reports, which can be updated automatically if data or analysis change. Instead of inserting a prefabricated graph or table into the report, the master document contains the R code necessary to obtain it. When run through R, all data analysis output (tables, graphs, etc.) is created on the fly and inserted into a final latex document. The report can be automatically updated if data or analysis change, which allows for truly reproducible research.

References in zbMATH (referenced in 18 articles )

Showing results 1 to 18 of 18.
Sorted by year (citations)

  1. Carugo, Oliviero (ed.); Eisenhaber, Frank (ed.): Data mining techniques for the life sciences (2016)
  2. Mathé, Ewy (ed.); Davis, Sean (ed.): Statistical genomics. Methods and protocols (2016)
  3. Heiberger, Richard M.; Holland, Burt: Statistical analysis and data display. An intermediate course with examples in R (2015)
  4. Beyersmann, Jan; Allignol, Arthur; Schumacher, Martin: Competing risks and multistate models with R (2012)
  5. Lenth, Russell; Højsgaard, Søren: Reproducible statistical analysis with multiple languages (2011)
  6. Rufibach, Kaspar: Selection models with monotone weight functions in meta analysis (2011)
  7. Vasishth, Shravan; Broe, Michael: The foundations of statistics: A simulation-based approach (2011)
  8. Horton, Nicholas J.; Kleinman, Ken: Using R for data management, statistical analysis, and graphics. (2010)
  9. Baggerly, Keith A.; Coombes, Kevin R.: Deriving chemosensitivity from cell lines: forensic bioinformatics and reproducible research in high-throughput biology (2009)
  10. Eckel, Sandrah P.; Peng, Roger D.: Interacting with local and remote data repositories using the stashR package (2009)
  11. Falcon, Seth: Caching code chunks in dynamic documents. The weaver package (2009)
  12. Göhlmann, Hinrich; Talloen, Willem: Gene expression studies using Affymetrix microarrays. (2009)
  13. Sawitzki, Günther: Computational statistics. An introduction to R (2009)
  14. Höhle, Michael: Surveillance: An R package for the monitoring of infectious diseases (2007)
  15. Gentleman, Robert: Reproducible research: a bioinformatics case study (2005)
  16. Hornik, Kurt; Leisch, Friederich: R Version 2.1.0 (2005)
  17. Hornik, Kurt: R: the next generation (2004)
  18. Ruschhaupt, Markus; Huber, Wolfgang; Poustka, Annemarie; Mansmann, Ulrich: A compendium to ensure computational reproducibility in high-dimensional classification tasks (2004)

Further publications can be found at: https://www.stat.uni-muenchen.de/~leisch/papers/fl-publications.html