Multiple imputation of missing data present in a dataset through the prediction based on either a random forest or a multinomial regression model. Covariates and time-dependent covariates can be included in the model. The prediction of the missing values is based on the method of Halpin (2012) <https://researchrepository.ul.ie/articles/report/Multiple_imputation_for_life-course_sequence_data/19839736>.
Version: | 2.1.0 |
Depends: | R (≥ 3.5.0) |
Imports: | Amelia, cluster, dfidx, doRNG, doSNOW, dplyr, foreach, graphics, mlr, nnet, parallel, plyr, ranger, rms, stats, stringr, TraMineR, TraMineRextras, utils, mice |
Suggests: | R.rsp, rmarkdown, testthat (≥ 3.0.0) |
Published: | 2024-11-13 |
Author: | Kevin Emery [aut, cre], Anthony Guinchard [aut], Andre Berchtold [aut], Kamyar Taher [aut] |
Maintainer: | Kevin Emery <kevin.emery at unige.ch> |
BugReports: | https://github.com/emerykevin/seqimpute/issues |
License: | GPL-2 |
URL: | https://github.com/emerykevin/seqimpute |
NeedsCompilation: | no |
Materials: | NEWS |
CRAN checks: | seqimpute results |
Reference manual: | seqimpute.pdf |
Vignettes: |
seqimpute vignette (source) |
Package source: | seqimpute_2.1.0.tar.gz |
Windows binaries: | r-devel: seqimpute_2.0.0.zip, r-release: seqimpute_2.0.0.zip, r-oldrel: seqimpute_2.0.0.zip |
macOS binaries: | r-release (arm64): seqimpute_2.0.0.tgz, r-oldrel (arm64): seqimpute_2.0.0.tgz, r-release (x86_64): seqimpute_2.0.0.tgz, r-oldrel (x86_64): seqimpute_2.0.0.tgz |
Old sources: | seqimpute archive |
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