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: 0.5.2
Depends: R (≥ 3.5.0)
Imports: stats, methods, FuzzySimRes, FuzzyNumbers, missForest, miceRanger, VIM, utils, FuzzyResampling, mice
Suggests: testthat (≥ 3.0.0)
Published: 2025年10月29日
Author: Maciej Romaniuk ORCID iD [cre, aut]
Maintainer: Maciej Romaniuk <mroman at ibspan.waw.pl>
License: GPL-3
NeedsCompilation: no
Materials: README

Documentation:

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macOS binaries: r-release (arm64): FuzzyImputationTest_0.5.2.tgz, r-oldrel (arm64): FuzzyImputationTest_0.5.2.tgz, r-release (x86_64): FuzzyImputationTest_0.5.2.tgz, r-oldrel (x86_64): FuzzyImputationTest_0.5.2.tgz

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