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seqimpute
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", "2.0.0")
Attach the package and use:
library("seqimpute")
Maintained by
Kevin Emery
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-09-08
Latest Update: 2022-11-07
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 2.0.0, https://cran.r-project.org/web/packages/seqimpute
Other packages that cited seqimpute R package
View seqimpute citation profile
Other R packages that seqimpute depends,
imports, suggests or enhances
Functions, R codes and Examples using
the seqimpute R package
Some associated functions: CO . COt . OD . seqQuickLook . seqTrans . seqimpute .
Some associated R codes: SI0_InitCheck.R . SI1_ORDERCreation.R . SI2_ComputeImputeOrder.R . SI3_SpecificModelImputation.R . SI4_InitialNAsImpute.R . SI5_TerminalNasImpute.R . SI6_SLGNAsImpute.R . SICommon.R . SIX_FinalConversion.R . seqQuickLook.R . seqTrans.R . seqimpute.R . Full seqimpute package functions and examples
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