Package: imputeR 2.2

imputeR: A General Multivariate Imputation Framework

Multivariate Expectation-Maximization (EM) based imputation framework that offers several different algorithms. These include regularisation methods like Lasso and Ridge regression, tree-based models and dimensionality reduction methods like PCA and PLS.

Authors:Steffen Moritz [aut, cre], Lingbing Feng [aut], Gen Nowak [ctb], Alan. H. Welsh [ctb], Terry. J. O'Neill [ctb]

imputeR_2.2.tar.gz
imputeR_2.2.zip(r-4.7)imputeR_2.2.zip(r-4.6)imputeR_2.2.zip(r-4.5)
imputeR_2.2.tgz(r-4.6-any)imputeR_2.2.tgz(r-4.5-any)
imputeR_2.2.tar.gz(r-4.7-any)imputeR_2.2.tar.gz(r-4.6-any)
imputeR_2.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
imputeR/json (API)

# Install 'imputeR' in R:

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

Bug tracker:https://github.com/steffenmoritz/imputer/issues

Datasets:

parkinson - Parkinsons Data Set
spect - SPECT Heart Data Set
tic - Insurance Company Benchmark (COIL 2000) Data Set

On CRAN:

missing-data

4.95 score 16 stars 56 scripts 545 downloads 1 mentions 28 exports 11 dependencies

Last updated from:beda0d1053. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	127
source / vignettes	OK	191
linux-release-x86_64	OK	132
macos-release-arm64	OK	79
macos-oldrel-arm64	OK	82
windows-devel	OK	95
windows-release	OK	84
windows-oldrel	OK	86
wasm-release	OK	115

Exports:CubistR Detect gbmC glmboostR guess impute lassoC lassoR major mixError mixGuess mr orderbox pcrR plotIm plsR ridgeC ridgeR Rmse rpartC SimEval SimIm stepBackC stepBackR stepBothC stepBothR stepForC stepForR

Dependencies:cli glue lifecycle magrittr plyr Rcpp reshape2 rlang stringi stringr vctrs

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
imputeR-package description	imputeR-package
Cubist method for imputation	CubistR
Detect variable type in a data matrix	Detect
boosting tree for imputation	gbmC
Boosting for regression	glmboostR
Impute by (educated) guessing	guess
General Imputation Framework in R	impute
logistic regression with lasso for imputation	lassoC
LASSO for regression	lassoR
Majority imputation for a vector	major
Calculate mixed error when the imputed matrix is mixed type	mixError
Naive imputation for mixed type data	mixGuess
calculate miss-classification error	mr
Ordered boxplot for a data matrix	orderbox
Parkinsons Data Set	parkinson
Principle component regression for imputation	pcrR
Plot function for imputation	plotIm
Partial Least Square regression for imputation	plsR
Ridge regression with lasso for imputation	ridgeC
Ridge shrinkage for regression	ridgeR
calculate the RMSE or NRMSE	Rmse
classification tree for imputation	rpartC
Evaluate imputation performance by simulation	SimEval
Introduce some missing values into a data matrix	SimIm
SPECT Heart Data Set	spect
Best subset for classification (backward)	stepBackC
Best subset (backward direction) for regression	stepBackR
Best subset for classification (both direction)	stepBothC
Best subset for regression (both direction)	stepBothR
Best subset for classification (forward direction)	stepForC
Best subset (forward direction) for regression	stepForR
Insurance Company Benchmark (COIL 2000) Data Set	tic