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# CITATION.cff file created with {cffr} R package
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cff-version: 1.2.0
message: 'To cite package "FuzzyLogit" in publications use:'
type: software
license: GPL-3.0-only
title: 'FuzzyLogit: Fuzzy Logistic Regression'
version: 0.1.1
doi: 10.32614/CRAN.package.FuzzyLogit
abstract: 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) <https://doi.org/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.
authors:
- family-names: Hasan
  given-names: Md Faruk
  email: md_faruk_hasan@sfu.ca
- family-names: Rahman
  given-names: Azizur
repository: https://cran.r-universe.dev
commit: 795946b75c072d3f9a38e6be87a3b2f41d2994b3
date-released: '2026-09-09'
contact:
- family-names: Hasan
  given-names: Md Faruk
  email: md_faruk_hasan@sfu.ca