Abstract
We present the cacher and CodeDepends packages for R, which provide tools for (1) caching and analyzing the code for statistical analyses and (2) distributing these analyses to others in an efficient manner over the web. The cacher package takes objects created by evaluating R expressions and stores them in key-value databases. These databases of cached objects can subsequently be assembled into “cache packages” for distribution over the web. The cacher package also provides tools to help readers examine the data and code in a statistical analysis and reproduce, modify, or improve upon the results. In addition, readers can easily conduct alternate analyses of the data. The CodeDepends package provides complementary tools for analyzing and visualizing the code for a statistical analysis and this functionality has been integrated into the cacher package. In this chapter we describe the cacher and CodeDepends packages and provide examples of how they can be used for reproducible research.
Disciplines
Numerical Analysis and Computation
Suggested Citation
Peng, Roger D. and Temple Lang, Duncan, "Caching and Visualizing Statistical Analyses" (June 2009). Johns Hopkins University, Dept. of Biostatistics Working Papers. Working Paper 193.
https://biostats.bepress.com/jhubiostat/paper193