seqimpute
Imputation of Missing Data in Sequence Analysis
v2.2.1
·
Jan 20, 2026
·
GPL-2
Description
Multiple imputation of missing data in a dataset using MICT or MICT-timing methods. The core idea of the algorithms is to fill gaps of missing data, which is the typical form of missing data in a longitudinal setting, recursively from their edges. Prediction is based on either a multinomial or random forest regression model. Covariates and time-dependent covariates can be included in the model.
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| Flavor | Status |
|---|---|
| r-devel-linux-x86_64-debian-clang | OK |
| r-devel-linux-x86_64-debian-gcc | OK |
| r-devel-linux-x86_64-fedora-clang | OK |
| r-devel-linux-x86_64-fedora-gcc | OK |
| r-devel-windows-x86_64 | OK |
| r-oldrel-macos-arm64 | OK |
| r-oldrel-macos-x86_64 | OK |
| r-oldrel-windows-x86_64 | OK |
| r-patched-linux-x86_64 | OK |
| r-release-linux-x86_64 | OK |
| r-release-macos-arm64 | OK |
| r-release-macos-x86_64 | OK |
| r-release-windows-x86_64 | OK |
Check History
OK 13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE May 2, 2026
ERROR 11 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE Apr 25, 2026
ERROR
r-release-macos-x86_64
package dependencies
Package required but not available: ‘mice’ See section ‘The DESCRIPTION file’ in the ‘Writing R Extensions’ manual.