State of the Art in Parallel Computing with R
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Abstract
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DOI: http://hdl.handle.net/10.18637/jss.v031.i01
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References listed on IDEAS
- Luke Tierney, 2009. "Code analysis and parallelizing vector operations in R," Computational Statistics, Springer, vol. 24(2), pages 217-223, May.
Citations
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Cited by:
- Andrew Karl & Randy Eubank & Jelena Milovanovic & Mark Reiser & Dennis Young, 2014. "Using RngStreams for parallel random number generation in C++ and R," Computational Statistics, Springer, vol. 29(5), pages 1301-1320, October.
- Manuel Eugster & Jochen Knaus & Christine Porzelius & Markus Schmidberger & Esmeralda Vicedo, 2011. "Hands-on tutorial for parallel computing with R," Computational Statistics, Springer, vol. 26(2), pages 219-239, June.
- Tomasz Górecki & Łukasz Smaga, 2019. "fdANOVA: an R software package for analysis of variance for univariate and multivariate functional data," Computational Statistics, Springer, vol. 34(2), pages 571-597, June.
- repec:jss:jstsof:35:i03 is not listed on IDEAS
- Bivand, Roger, 2010. "Exploiting Parallelization in Spatial Statistics: an Applied Survey using R," Discussion Paper Series in Economics 25/2010, Norwegian School of Economics, Department of Economics.
- repec:jss:jstsof:37:i03 is not listed on IDEAS
- Philippe Pébay & Timothy B. Terriberry & Hemanth Kolla & Janine Bennett, 2016. "Numerically stable, scalable formulas for parallel and online computation of higher-order multivariate central moments with arbitrary weights," Computational Statistics, Springer, vol. 31(4), pages 1305-1325, December.
- repec:jss:jstsof:39:c01 is not listed on IDEAS
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