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FuzzyResampling
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Download and install FuzzyResampling package within the R console
Install from CRAN:
install.packages("FuzzyResampling")
Install from Github:
library("remotes")
install_github("cran/FuzzyResampling") Install by package version:
library("remotes")
install_version("FuzzyResampling", "0.6.4") Attach the package and use:
library("FuzzyResampling")
Maintained by
Maciej Romaniuk
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First Published: 2021-09-15
Latest Update: 2024-10-04
Description:
The classical (i.e. Efron's, see Efron and Tibshirani (1994, ISBN:978-0412042317) "An Introduction to the Bootstrap") bootstrap is widely used for both the real (i.e. "crisp") and fuzzy data.
The main aim of the algorithms implemented in this package is to overcome a problem with repetition of a few distinct values and to create fuzzy numbers, which are "similar" (but not the same) to values from the initial sample.
To do this, different characteristics of triangular/trapezoidal numbers are kept (like the value, the ambiguity, etc., see Grzegorzewski et al. , Grzegorzewski et al. (2020) , Grzegorzewski et al. (2020) , Grzegorzewski and Romaniuk (2022) , Romaniuk and Hryniewicz (2019) ).
Some additional procedures related to these resampling methods are also provided,
like calculation of the Bertoluzza et al.'s distance (aka the mid/spread distance, see Bertoluzza et al. (1995) "On a new class of distances between fuzzy numbers")
and estimation of the p-value of the one- and two- sample bootstrapped test for the mean (see Lubiano et al. (2016, )).
Additionally, there are procedures which randomly generate trapezoidal fuzzy numbers using some well-known statistical distributions.
How to cite:
Maciej Romaniuk (2021). FuzzyResampling: Resampling Methods for Triangular and Trapezoidal Fuzzy Numbers. R package version 0.6.4, https://cran.r-project.org/web/packages/FuzzyResampling. Accessed 15 Jul. 2026.
Previous versions and publish date:
0.1.0 (2021-09-15 20:40), 0.3.0 (2021-11-22 08:50), 0.3.1 (2021-12-14 15:40), 0.4.0 (2022-01-05 07:20), 0.4.1 (2022-03-08 12:20), 0.4.2 (2022-03-21 10:40), 0.5.0 (2022-12-02 11:00), 0.6.0 (2022-12-15 10:30), 0.6.1 (2023-08-08 10:40), 0.6.2 (2023-09-25 13:00), 0.6.3 (2023-11-22 12:20), (2026-07-09 08:04)
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Complete documentation for FuzzyResampling
Functions, R codes and Examples using
the FuzzyResampling R package
Some associated functions: BertoluzzaDistance . CalculateAmbiguity . CalculateAmbiguityL . CalculateAmbiguityR . CalculateExpValue . CalculateFuzziness . CalculateValue . CalculateWidth . ClassicalBootstrap . ComparePowerOneSampleCTest . ComparisonOneSampleCTest . ComparisonSEMean . DMethod . EWMethod . FuzzyResampling-package . GeneratorFuzzyNumbers . GeneratorNExpUU . GeneratorNU . OneSampleCTest . SEResamplingMean . TwoSampleCTest . VAAMethod . VAFMethod . VAMethod . WMethod . resamplingMethods . samplingGenerators .
Some associated R codes: BertoluzzaDistance.R . CalculateAmbiguity.R . CalculateAmbiguityL.R . CalculateAmbiguityR.R . CalculateExpValue.R . CalculateFuzziness.R . CalculateValue.R . CalculateWidth.R . ClassicalBoostrap.R . ComparePowerOneSampleCTest.R . ComparisonOneSampleCTest.R . ComparisonSEMean.R . DMethod.R . EWMethod.R . FuzzyResampling-package.R . GeneratorFuzzyNumbers.R . GeneratorNExpUU.R . GeneratorNU.R . OneSampleCTest.R . SEResamplingMean.R . TwoSampleCTest.R . VAAMethod.R . VAFMethod.R . VAMethod.R . WMethod.R . resamplingMethods.R . samplingGenerators.R . utils.R . Full FuzzyResampling package functions and examples
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