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seqimpute  

Imputation of Missing Data in Sequence Analysis
View on CRAN: Click here


Download and install seqimpute package within the R console
Install from CRAN:
install.packages("seqimpute")

Install from Github:
library("remotes")
install_github("cran/seqimpute")

Install by package version:
library("remotes")
install_version("seqimpute", "2.2.1")



Attach the package and use:
library("seqimpute")
Maintained by
Kevin Emery
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-09-08
Latest Update: 2025-01-15
Description:
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) .
How to cite:
Kevin Emery (2022). seqimpute: Imputation of Missing Data in Sequence Analysis. R package version 2.2.1, https://cran.r-project.org/web/packages/seqimpute. Accessed 05 Mar. 2026.
Previous versions and publish date:
1.7 (2022-09-08 11:00), 1.8 (2022-11-07 14:10), 2.0.0 (2024-03-27 14:00), 2.1.0 (2024-11-13 13:20), 2.2.0 (2025-01-15 17:10)
Other packages that cited seqimpute R package
View seqimpute citation profile
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Complete documentation for seqimpute
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