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: |
0.5.0 |
Depends: |
R (≥ 3.5.0) |
Imports: |
stats, methods, FuzzySimRes, FuzzyNumbers, missForest, miceRanger, VIM, utils, FuzzyResampling, mice |
Suggests: |
testthat (≥ 3.0.0) |
Published: |
2025-03-26 |
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:
Downloads:
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