Package: mrregression 1.0.0

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>.

Authors:Esther Denecke [aut], Leo N. Geppert [aut, cre], Steffen Maletz [ctb], R Core Team [ctb]

mrregression_1.0.0.tar.gz
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manual.pdf |manual.html
DESCRIPTION
card.svg |card.png
mrregression/json (API)

# Install 'mrregression' in R:
install.packages('mrregression', repos = c('https://lgstat.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 254 downloads 2 exports 2 dependencies

Last updated from:be37e69f6a. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK145
source / vignettesOK164
linux-release-x86_64OK130
macos-release-arm64OK125
macos-oldrel-arm64OK89
windows-develOK100
windows-releaseOK105
windows-oldrelOK100
wasm-releaseOK146

Exports:mrbayesmrfrequentist

Dependencies:data.tableRcpp

Readme and manuals

Help Manual

Help pageTopics
Simulated Example DataexampleData
Bayesian linear regression using Merge and Reducemrbayes
Fitting frequentist linear models using Merge and Reducemrfrequentist
mrregression: Frequentist and Bayesian linear regression using Merge and Reduce.coef.mrfrequentist mrregression nobs.mrbayes nobs.mrfrequentist predict.mrfrequentist print.summary.mrbayes print.summary.mrfrequentist summary.mrbayes summary.mrfrequentist