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FuzzyImputationTest  

Imputation Procedures and Quality Tests for Fuzzy Data
View on CRAN: Click here


Download and install FuzzyImputationTest package within the R console
Install from CRAN:
install.packages("FuzzyImputationTest")

Install from Github:
library("remotes")
install_github("cran/FuzzyImputationTest")

Install by package version:
library("remotes")
install_version("FuzzyImputationTest", "0.5.2")



Attach the package and use:
library("FuzzyImputationTest")
Maintained by
Maciej Romaniuk
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2024-09-09
Latest Update: 2025-05-15
Description:
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. "Fuzzy Data Imputation with DIMP and FGAIN" RB/23/2023 (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.
How to cite:
Maciej Romaniuk (2024). FuzzyImputationTest: Imputation Procedures and Quality Tests for Fuzzy Data. R package version 0.5.2, https://cran.r-project.org/web/packages/FuzzyImputationTest. Accessed 08 Mar. 2026.
Previous versions and publish date:
0.2.0 (2024-09-09 11:00), 0.3.0 (2024-09-27 14:10), 0.3.3 (2024-10-09 09:00), 0.3.4 (2024-10-30 09:40), 0.3.6 (2024-12-11 11:50), 0.3.8 (2024-12-20 05:50), 0.4.0 (2025-01-24 16:20), 0.5.0 (2025-03-26 09:00), 0.5.1 (2025-05-15 09:50)
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Complete documentation for FuzzyImputationTest
Functions, R codes and Examples using the FuzzyImputationTest R package
Full FuzzyImputationTest package functions and examples
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