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FuzzyLogit
View on CRAN: Click
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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
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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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