Imputation Procedures and Quality Tests for Fuzzy Data R package FuzzyImputationTest version 0.5.2 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. Software Depends: R (>= 3.5.0) Imports: stats, methods, FuzzySimRes, FuzzyNumbers, missForest, miceRanger, VIM, utils, FuzzyResampling, mice Suggests: testthat (>= 3.0.0) Maciej Romaniuk <mroman@ibspan.waw.pl> Comprehensive R Archive Network (CRAN) Maciej Romaniuk [cre, aut] (ORCID: <https://orcid.org/0000-0001-9649-396X>) GPL-3 2025-10-29 application/tgz https://CRAN.R-project.org/package=FuzzyImputationTest doi:10.32614/CRAN.package.FuzzyImputationTest