From ee475f103f514905d3ed9c3a5dd7b2cacbc46021 Mon Sep 17 00:00:00 2001 From: wlandau-lilly Date: Fri, 10 Nov 2017 09:27:34 -0500 Subject: [PATCH] Edit notes on reproducibility --- README.md | 2 +- vignettes/drake.Rmd | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index aad5e64f0..83729d519 100644 --- a/README.md +++ b/README.md @@ -211,7 +211,7 @@ Please refer to [TROUBLESHOOTING.md](https://github.com/wlandau-lilly/drake/blob # Reproducibility -There is room to improve the conversation and the landscape of reproducibility in the R and Statistics communities. At a more basic level than scientific replicability, literate programming, and version control, reproducibility carries an implicit promise that the alleged results of an analysis really do match the code. Drake helps keep this promise by tracking the relationships among the components of the analysis, a rare and effective approach that also saves time. +There is room to improve the conversation and the landscape of reproducibility in the R and Statistics communities. At a more basic level than scientific replicability, literate programming, and version control, reproducibility carries an implicit promise that alleged computational results really do match the generating code. To reinforce this promise, drake fingerprints and watches dependencies and output, skipping computations that are already up to date. ```r library(drake) diff --git a/vignettes/drake.Rmd b/vignettes/drake.Rmd index e2b96fda1..7db926014 100644 --- a/vignettes/drake.Rmd +++ b/vignettes/drake.Rmd @@ -208,7 +208,7 @@ Please refer to [TROUBLESHOOTING.md](https://github.com/wlandau-lilly/drake/blob # Reproducibility -There is room to improve the conversation and the landscape of reproducibility in the R and Statistics communities. At a more basic level than scientific replicability, literate programming, and version control, reproducibility carries an implicit promise that the alleged results of an analysis really do match the code. Drake helps keep this promise by tracking the relationships among the components of the analysis, a rare and effective approach that also saves time. +There is room to improve the conversation and the landscape of reproducibility in the R and Statistics communities. At a more basic level than scientific replicability, literate programming, and version control, reproducibility carries an implicit promise that alleged computational results really do match the generating code. To reinforce this promise, drake fingerprints and watches dependencies and output, skipping computations that are already up to date. ```{r reproducibilitydrakermd, eval = FALSE} library(drake)