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This paper explores the ecosystem of software packages for R, one of the most popular environments for statistical computing today. We empirically study how R packages are developed and distributed on different repositories: CRAN, BioConductor, R-Forge and GitHub. We also explore the role and size of each repository, the inter-repository dependencies, and how these repositories grow over time. With this analysis, we provide a deeper insight into the extent and the evolution of the R package ecosystem.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 16 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
| views | 229 | |
| downloads | 67 |

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