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]

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mrregression/json (API)

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

Peer review:

Datasets:

On CRAN:

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

2 exports 0.00 score 2 dependencies 161 downloads

Last updated 4 years agofrom:be37e69f6a. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 02 2024
R-4.5-winNOTESep 02 2024
R-4.5-linuxNOTESep 02 2024
R-4.4-winNOTESep 02 2024
R-4.4-macNOTESep 02 2024
R-4.3-winNOTESep 02 2024
R-4.3-macNOTESep 02 2024

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