CRAN/E | seqimpute

seqimpute

Imputation of Missing Data in Sequence Analysis

Installation

About

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) .

Key Metrics

Version 2.0.0
R ≥ 3.5.0
Published 2024-03-27 30 days ago
Needs compilation? no
License GPL-2
CRAN checks seqimpute results

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Maintainer

Maintainer

Kevin Emery

kevin.emery@unige.ch

Authors

Kevin Emery

aut / cre

Anthony Guinchard

aut

Andre Berchtold

aut

Kamyar Taher

aut

Material

NEWS
Reference manual
Package source

Vignettes

seqimpute vignette

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

seqimpute archive

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