

Implementing Reproducible Research by Victoria Stodden
In computational science, reproducibility requires that researchers make code and data available to others so that the data can be analyzed in a similar manner as in the original publication. Code must be available to be distributed, data must be accessible in a readable format, and a platform must be available for widely distributing the data and code. In addition, both data and code need to be licensed permissively enough so that others can reproduce the work without a substantial legal burden.
Implementing Reproducible Research covers many of the elements necessary for conducting and distributing reproducible research. It explains how to accurately reproduce a scientific result.
Divided into three parts, the book discusses the tools, practices, and dissemination platforms for ensuring reproducibility in computational science. It describes:
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- Computational tools, such as Sweave, knitr, VisTrails, Sumatra, CDE, and the Declaratron system
- Open source practices, good programming practices, trends in open science, and the role of cloud computing in reproducible research
- Software and methodological platforms, including open source software packages, RunMyCode platform, and open access journals
Each part presents contributions from leaders who have developed software and other products that have advanced the field. Supplementary material is available at www.ImplementingRR.org.
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Advanced R
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Using R for Introductory Statistics
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Analyzing Baseball Data with R
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Analyzing Baseball Data with R, Second Edition
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Introduction to Scientific Programming and Simulation Using R
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Reproducible Research with R and R Studio
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Mastering data.table in R
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Testing R Code
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Statistical Inference via Data Science: A ModernDive into R and the Tidyverse
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Using R for Bayesian Spatial and Spatio-Temporal Health Modeling
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The Essentials of Data Science: Knowledge Discovery Using R
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R and MATLAB
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Growth Curve Analysis and Visualization Using R
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Dose-Response Analysis Using R
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Spatial Analysis in Geology Using R
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Using the R Commander
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Behavior Analysis with Machine Learning Using R
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blogdown
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Javascript for R
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Using R for Modelling and Quantitative Methods in Fisheries
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Distributions for Modeling Location, Scale, and Shape
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Introduction to Political Analysis in R
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Introductory Fisheries Analyses with R
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Basics of Matrix Algebra for Statistics with R
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R Graphics
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Modeling Data with Functional Programming in R, Volume 1
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Statistical Genetics
| SKU | Unavailable |
| ISBN 13 | |
| ISBN 10 | |
| Title | Implementing Reproducible Research |
| Author | Victoria Stodden |
| Series | |
| Condition | Unavailable |
| Binding Type | |
| Publisher | |
| Year published | |
| Number of pages | |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |
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