Package: DIRMR 0.5.0
Guangbao Guo
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:
DIRMR_0.5.0.tar.gz
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://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 3 hours agofrom:3c7ad07359. Checks:OK: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 26 2024 |
| R-4.5-linux | OK | Nov 26 2024 |
Exports:DECMEDEMDMCEMDMOPXEMDPXEMECMEEMMCEMMOPXEMPXEM
Dependencies:clicodetoolsdigestfuturefuture.applyglobalslatticelavalistenvMASSMatrixmvtnormnumDerivparallellyprogressrSQUAREMsurvival
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Hox pupil popularity data | data |
| DECME | DECME |
| DEM | DEM |
| Hox pupil popularity data with missing popularity scores | df1 |
| DMCEM | DMCEM |
| DMOPXEM | DMOPXEM |
| DPXEM | DPXEM |
| ECME | ECME |
| EM | EM |
| MCEM | MCEM |
| MOPXEM | MOPXEM |
| PXEM | PXEM |
