FuzzyImputationTest: Imputation Procedures and Quality Tests for Fuzzy Data

Special procedures for the imputation of missing fuzzy numbers are still underdeveloped. The goal of the package is to provide the new d-imputation method (DIMP for short, Romaniuk, M. and Grzegorzewski, P. (2023) "Fuzzy Data Imputation with DIMP and FGAIN" RB/23/2023) and covert some classical ones applied in R packages ('missForest','miceRanger','knn') for use with fuzzy datasets. Additionally, specially tailored benchmarking tests are provided to check and compare these imputation procedures with fuzzy datasets.

Version:	0.3.4
Depends:	R (≥ 3.5.0)
Imports:	stats, methods, FuzzySimRes, FuzzyNumbers, missForest, miceRanger, VIM, utils
Suggests:	testthat (≥ 3.0.0)
Published:	2024-10-30
DOI:	10.32614/CRAN.package.FuzzyImputationTest
Author:	Maciej Romaniuk [cre, aut]
Maintainer:	Maciej Romaniuk <mroman at ibspan.waw.pl>
License:	GPL-3
NeedsCompilation:	yes
Materials:	README
CRAN checks:	FuzzyImputationTest results

Documentation:

Reference manual:

FuzzyImputationTest.pdf

Downloads:

Package source:	FuzzyImputationTest_0.3.4.tar.gz
Windows binaries:	r-devel: FuzzyImputationTest_0.3.4.zip, r-release: FuzzyImputationTest_0.3.4.zip, r-oldrel: FuzzyImputationTest_0.3.4.zip
macOS binaries:	r-release (arm64): FuzzyImputationTest_0.3.4.tgz, r-oldrel (arm64): FuzzyImputationTest_0.3.4.tgz, r-release (x86_64): FuzzyImputationTest_0.3.4.tgz, r-oldrel (x86_64): FuzzyImputationTest_0.3.4.tgz
Old sources:	FuzzyImputationTest archive

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