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FuzzyLogit  

Fuzzy Logistic Regression
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("FuzzyLogit", "0.1.1")



Attach the package and use:
library("FuzzyLogit")
Maintained by
Md Faruk Hasan
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-09-09
Latest Update: 2026-09-09
Description:
Fits logistic regression models in which the binary response is represented by a triangular fuzzy number rather than an exact crisp label, allowing uncertainty in class membership to be encoded directly in the outcome. Model parameters are estimated using the Fuzzy Least Squares approach of Diamond (1988) <doi:10.1016/0020-0255(88)90047-3>, following the integrated fuzzy logistic regression method of Yapici Pehlivan and Sahin (2018) <https://dergipark.org.tr/en/pub/jssa/issue/37877/437725>. Provides fitting, prediction, classification, cross-validation, and diagnostic plotting methods, along with tools for comparing model behaviour across different assumed levels of label uncertainty.
How to cite:
Md Faruk Hasan (2026). FuzzyLogit: Fuzzy Logistic Regression. R package version 0.1.1, https://cran.r-project.org/web/packages/FuzzyLogit. Accessed 24 Oct. 2026.
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Complete documentation for FuzzyLogit
Functions, R codes and Examples using the FuzzyLogit R package
Full FuzzyLogit package functions and examples
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