R2WinBUGS: A Package for Running WinBUGS from R

By S. Sturtz, Uwe Ligges, Andrew Gelman. 2005

1,747 citations recorded by the source corpus.

The R2WinBUGS package provides convenient functions to call WinBUGS from R. It automatically writes the data and scripts in a format readable by WinBUGS for processing in batch mode, which is possible since version 1.4. After the WinBUGS process has finished, it is possible either to read the resulting data into R by the package itself--which gives a compact graphical summary of inference and convergence diagnostics--or to use the facilities of the coda package for further analyses of the output. Examples are given to demonstrate the usage of this package.

Subfields: Artificial Intelligence, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/dd8bfb80f22ba89ae4a0b6c9721a954c29b351f2

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Citations in the corpus

Bayesian Analysis for Penalized Spline Regression Using WinBUGS (2005, methodology): “R2WinBUGS is an R package developed by Sturtz, Ligges and Gelman [25] that calls WinBUGS 1.”
Guidelines for a graph-theoretic implementation of structural equation modeling (2012, methodology): “As stated above, estimation was performed using WinBUGS (Lunn et al. 2000) implemented through the R package R2winbugs (Sturtz et al. 2005).”
Human development and climate affect hibernation in a large carnivore with implications for human–carnivore conflicts (2018, neutral): “5 to 5°C under medium–low emissions scenarios and by 3.5 to 6.5°C under high emissions scenarios (Gordon & Ojima, 2015). Assuming that the relationship we observed between temperature and hibernation length is temporally consistent, where a 1°C increase in the winter minimum temperature is associate”
The Effects of Menstrual Cycle Phase on Exercise Performance in Eumenorrheic Women: A Systematic Review and Meta-Analysis (2020, methodology): “Analyses were performed using the R packages R2WinBUGS [51] and brms [52].”
An Analysis of the New York City Police Department's “Stop-and-Frisk” Policy in the Context of Claims of Racial Bias (2007, methodology): “Computations were easily performed using the Bayesian software BUGS (Spiegelhalter, Thomas, Best, Gilks, and Lunn 1994, 2003), which implements Markov chain Monte Carlo simulation from R (R Project 2000; Sturtz, Ligges, and Gelman 2005).”