Package: DIRMR 0.5.0

DIRMR: Distributed Imputation for Random Effects Models with Missing Responses

By adding over-relaxation factor to PXEM (Parameter Expanded Expectation Maximization) method, the MOPXEM (Monotonically Overrelaxed Parameter Expanded Expectation Maximization) method is obtained. Compare it with the existing EM (Expectation-Maximization)-like methods. Then, distribute and process five methods and compare them, achieving good performance in convergence speed and result quality.The philosophy of the package is described in Guo G. (2022) <doi:10.1007/s00180-022-01270-z>.

Authors:Guangbao Guo [aut, cre], Yaping Li [aut]

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DIRMR.pdf |DIRMR.html✨
DIRMR/json (API)

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

Peer review:

Datasets:
  • data - Hox pupil popularity data
  • df1 - Hox pupil popularity data with missing popularity scores

On CRAN:

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

1.00 score 10 exports 17 dependencies

Last updated 23 hours agofrom:3c7ad07359. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 27 2024
R-4.5-winOKNov 27 2024
R-4.5-linuxOKNov 27 2024
R-4.4-winOKNov 27 2024
R-4.4-macOKNov 27 2024
R-4.3-winOKNov 27 2024
R-4.3-macOKNov 27 2024

Exports:DECMEDEMDMCEMDMOPXEMDPXEMECMEEMMCEMMOPXEMPXEM

Dependencies:clicodetoolsdigestfuturefuture.applyglobalslatticelavalistenvMASSMatrixmvtnormnumDerivparallellyprogressrSQUAREMsurvival