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mrregression: Regression Analysis for Very Large Data Sets via Merge and Reduce

Frequentist and Bayesian linear regression for large data sets. Useful when the data does not fit into memory (for both frequentist and Bayesian regression), to make running time manageable (mainly for Bayesian regression), and to reduce the total running time because of reduced or less severe memory-spillover into the virtual memory. This is an implementation of Merge & Reduce for linear regression as described in Geppert, L.N., Ickstadt, K., Munteanu, A., & Sohler, C. (2020). 'Streaming statistical models via Merge & Reduce'. International Journal of Data Science and Analytics, 1-17, <doi:10.1007/s41060-020-00226-0>.

Version: 1.0.0
Depends: R (≥ 4.0.0), Rcpp (≥ 1.0.5)
Imports: data.table (≥ 1.12.8)
Suggests: testthat (≥ 2.3.2)
Enhances: rstan (≥ 2.19.3)
Published: 2020-09-22
DOI: 10.32614/CRAN.package.mrregression
Author: Esther Denecke [aut], Leo N. Geppert [aut, cre], Steffen Maletz [ctb], R Core Team [ctb]
Maintainer: Leo N. Geppert <geppert at statistik.uni-dortmund.de>
License: GPL-2 | GPL-3
NeedsCompilation: no
CRAN checks: mrregression results

Documentation:

Reference manual: mrregression.pdf

Downloads:

Package source: mrregression_1.0.0.tar.gz
Windows binaries: r-devel: mrregression_1.0.0.zip, r-release: mrregression_1.0.0.zip, r-oldrel: mrregression_1.0.0.zip
macOS binaries: r-release (arm64): mrregression_1.0.0.tgz, r-oldrel (arm64): mrregression_1.0.0.tgz, r-release (x86_64): mrregression_1.0.0.tgz, r-oldrel (x86_64): mrregression_1.0.0.tgz

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.