Package: deepImp 1.1.0

Matthias Templ

deepImp: Imputation with Deep Learning Methods

Imputation of mixed-type and compositional data with neural networks. The architecture (number and size of hidden layers, dropout, activation, optimiser) is user-configurable. See Templ (2021) <doi:10.1007/978-3-030-71175-7>.

Authors:Matthias Templ [aut, cre]

deepImp_1.1.0.tar.gz
deepImp_1.1.0.tar.gz(r-4.7-any)deepImp_1.1.0.tar.gz(r-4.6-any)
deepImp_1.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
deepImp/json (API)
NEWS

# Install 'deepImp' in R:

install.packages('deepImp', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

beer - Beer ageing volatile-compound data

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.70 score 7 exports 160 dependencies

Last updated from:1738ec5127. Checks:4 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	429
source / vignettes	OK	365
linux-release-x86_64	OK	254
wasm-release	OK	163

Exports:deepimp_arch deepimp_arch_small getImputed guessType impNNet impNNetCoDa new_deepimp

Dependencies:abind ash backports bbotk bit bit64 bitops boot broom callr car carData checkmate class cli cluster codetools colorspace coro cowplot cpp11 crayon cvTools data.table DEoptimR Deriv desc deSolve digest doBy dplyr e1071 evaluate farver fda fds FNN forcats forecast Formula fracdiff fs future future.apply generics GGally ggfortify ggplot2 ggstats globals glue gridExtra gtable hdrcde hms isoband jsonlite kernlab KernSmooth ks labeling laeken lattice lgr lifecycle listenv lme4 lmtest locfit luz magrittr MASS Matrix MatrixModels mclust mgcv microbenchmark minqa mirai mlbench mlr3 mlr3learners mlr3measures mlr3misc mlr3pipelines mlr3tuning modelr multicool mvtnorm nanonext nlme nloptr nnet numDeriv otel palmerpenguins paradox parallelly patchwork pbkrtest pcaPP perry pillar pkgconfig pls plyr pracma prettyunits processx progress proxy PRROC ps purrr quantreg R6 rainbow ranger rbibutils RColorBrewer Rcpp RcppArmadillo RcppEigen RCurl Rdpack reformulas reshape2 rlang robCompositions robustbase robustHD rrcov rsvd S7 safetensors scales sp SparseM sparsepca stringi stringr survival tibble tidyr tidyselect timeDate torch truncnorm urca utf8 uuid vcd vctrs VIM viridisLite withr xgboost zCompositions zeallot zoo

Neural-network imputation with deepImp

Rendered fromdeepImp.Rmdusingknitr::rmarkdownon Jun 10 2026.

Last update: 2026-06-10
Started: 2026-06-10

Citation

Readme and manuals

Help Manual

Help page	Topics
Beer ageing volatile-compound data	beer
Architecture configuration for neural-network imputation	deepimp_arch deepimp_arch_small
Extract imputed data from a deepimp object	getImputed
Guess the measurement type of each variable	guessType
Neural-network imputation for mixed-type data	impNNet
Neural-network imputation of rounded zeros in compositional data	impNNetCoDa
Construct a deepimp object	new_deepimp