Other packages > Find by keyword >

FuzzyResampling  

Resampling Methods for Triangular and Trapezoidal Fuzzy Numbers
View on CRAN: Click here


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
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-09-15
Latest Update: 2023-11-22
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 22 Dec. 2024.
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)
Other packages that cited FuzzyResampling R package
View FuzzyResampling citation profile
Other R packages that FuzzyResampling depends, imports, suggests or enhances
Complete documentation for FuzzyResampling
Downloads during the last 30 days
Get rewarded with contribution points by helping add
Reviews / comments / questions /suggestions ↴↴↴

Today's Hot Picks in Authors and Packages

elect  
Estimation of Life Expectancies Using Multi-State Models
Functions to compute state-specific and marginal life expectancies. The computation is based on a fi ...
Download / Learn more Package Citations See dependency  
Rfast2  
A Collection of Efficient and Extremely Fast R Functions II
A collection of fast statistical and utility functions for data analysis. Functions for regression, ...
Download / Learn more Package Citations See dependency  
composits  
Compositional, Multivariate and Univariate Time Series Outlier Ensemble
A compositional multivariate and univariate time series outlier ensemble.It uses the four R packages ...
Download / Learn more Package Citations See dependency  
wordspace  
Distributional Semantic Models in R
An interactive laboratory for research on distributional semantic models ('DSM', see < ...
Download / Learn more Package Citations See dependency  
LOGANTree  
Tree-Based Models for the Analysis of Log Files from Computer-Based Assessments
Enables researchers to model log-file data from computer-based assessments using machine-learning te ...
Download / Learn more Package Citations See dependency  
Maintainer: Qi Qin (view profile)
dmlalg  
Double Machine Learning Algorithms
Implementation of double machine learning (DML) algorithms in R, based on Emmenegger and Buehlmann ...
Download / Learn more Package Citations See dependency  

23,394

R Packages

201,798

Dependencies

63,416

Author Associations

23,395

Publication Badges

© Copyright 2022 - present. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA