Package: FuzzyImputationTest 0.3.5

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.

Authors:Maciej Romaniuk [cre, aut]

FuzzyImputationTest_0.3.5.tar.gz
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FuzzyImputationTest.pdf |FuzzyImputationTest.html✨
FuzzyImputationTest/json (API)

# Install 'FuzzyImputationTest' in R:
install.packages('FuzzyImputationTest', repos = c('https://mroman-ibs.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/mroman-ibs/fuzzyimputationtest/issues

On CRAN:

3.70 score 2 scripts 302 downloads 22 exports 119 dependencies

Last updated 23 days agofrom:ec44521da7. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 31 2024
R-4.5-winOKOct 31 2024
R-4.5-linuxOKOct 31 2024
R-4.4-winOKOct 31 2024
R-4.4-macOKOct 31 2024
R-4.3-winOKOct 31 2024
R-4.3-macOKOct 31 2024

Exports:ApplyStatisticalTestsCalculateFuzzyMeasuresdistanceNamesErrorMatrixerrorTypesFuzzifyMatrixFuzzyImputationFuzzyNumbersToMatrixImputationDimpImputationTestsIntroducingNAMatrixToFuzzyNumbersMeasureAHDMeasureEuclideanMeasureHSDmeasuresTypesmethodNamesMethodsComparisonRemoveNotFuzzysetsNamesStatisticalMeasurestestsNames

Dependencies:abindaskpassbackportsbootbroomcarcarDatacellrangerclassclicodetoolscolorspacecorrplotcowplotcpp11crayoncurldata.tableDEoptimRDerivDescToolsdigestdoBydoRNGdplyre1071ExactexpmfansifarverFNNforeachFormulaFuzzyNumbersFuzzySimResgenericsggplot2ggpubrggrepelggsciggsignifgldglmnetgluegridExtragtablehmshttrisobanditeratorsitertoolsjsonlitelabelinglaekenlatticelifecyclelme4lmomlmtestmagrittrMASSMatrixMatrixModelsmgcvmiceRangermicrobenchmarkmimeminqamissForestmodelrmunsellmvtnormnlmenloptrnnetnumDerivopensslpalassopbkrtestpillarpkgconfigpolynomprettyunitsprogressproxypurrrquantregR6randomForestrangerRColorBrewerRcppRcppEigenreadxlrematchrlangrngtoolsrobustbaserootSolverstatixrstudioapiscalesshapespSparseMstringistringrsurvivalsystibbletidyrtidyselectutf8vcdvctrsVIMviridisLitewithrzoo

Readme and manuals

Help Manual

Help pageTopics
Statistical epistemic tests the imputed values.ApplyStatisticalTests
Calculation of the fuzzy measures for the imputed values.CalculateFuzzyMeasures
A vector containing names of the calculated distance measures between fuzzy numbers.distanceNames
Calculation of the errors for the imputed values.ErrorMatrix
A vector containing names of the types of the calculated errors.errorTypes
Fuzzyfing the crisp values.FuzzifyMatrix
Main method to impute fuzzy values.FuzzyImputation
Conversion of a list of fuzzy numbers into a matrix.FuzzyNumbersToMatrix
DIMP (d-imputation) method for fuzzy numbers.ImputationDimp
Battery of test for the imputed fuzzy values.ImputationTests
Introducing NAs to the specified matrix.IntroducingNA
Conversion of a matrix to a list of fuzzy numbers.MatrixToFuzzyNumbers
Function to calculate the AHD distance between two fuzzy numbers.MeasureAHD
Function to calculate the Euclidean distance between two fuzzy numbers.MeasureEuclidean
Function to calculate the HSD distance between two fuzzy numbers.MeasureHSD
A vector containing names of the types of the calculated statistical measures.measuresTypes
A vector containing names of the resampling methods.methodNames
Comparison of imputation methods for fuzzy values.MethodsComparison
Removing values that are not fuzzy numbers.RemoveNotFuzzy
A vector containing names of the subsets used in the epistemic tests.setsNames
Calculation of statistical measures for errors of the imputed data.StatisticalMeasures
A vector containing names of the types of the applied epistemic tests.testsNames