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]

DIRMR_0.5.0.tar.gz
DIRMR_0.5.0.zip(r-4.5)DIRMR_0.5.0.zip(r-4.4)DIRMR_0.5.0.zip(r-4.3)
DIRMR_0.5.0.tgz(r-4.5-any)DIRMR_0.5.0.tgz(r-4.4-any)DIRMR_0.5.0.tgz(r-4.3-any)
DIRMR_0.5.0.tar.gz(r-4.5-noble)DIRMR_0.5.0.tar.gz(r-4.4-noble)
DIRMR_0.5.0.tgz(r-4.4-emscripten)DIRMR_0.5.0.tgz(r-4.3-emscripten)
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'))
Datasets:
  • data - Hox pupil popularity data
  • df1 - Hox pupil popularity data with missing popularity scores

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 153 downloads 10 exports 17 dependencies

Last updated 4 months agofrom:3c7ad07359. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 27 2025
R-4.5-winOKMar 27 2025
R-4.5-macOKMar 27 2025
R-4.5-linuxOKMar 27 2025
R-4.4-winOKMar 27 2025
R-4.4-macOKMar 27 2025
R-4.4-linuxOKMar 27 2025
R-4.3-winOKMar 27 2025
R-4.3-macOKMar 27 2025

Exports:DECMEDEMDMCEMDMOPXEMDPXEMECMEEMMCEMMOPXEMPXEM

Dependencies:clicodetoolsdigestfuturefuture.applyglobalslatticelavalistenvMASSMatrixmvtnormnumDerivparallellyprogressrSQUAREMsurvival