IFARIMA: Intuitionistic Fuzzy Autoregressive Integrated Moving Average Model

The Intuitionistic Fuzzy Autoregressive Integrated Moving Average model offers advanced time series forecasting by integrating intuitionistic fuzzy sets with ARIMA. It enhances prediction accuracy by handling uncertainties and hesitations more effectively than traditional models, making it ideal for complex, real-world data applications. The package has been developed using the algorithm of Yolcu and Yolcu (2023) <doi:10.1016/j.eswa.2022.119336>.

Version:	0.1.0
Imports:	stats, forecast
Suggests:	testthat (≥ 3.0.0)
Published:	2026-10-29
DOI:	10.32614/CRAN.package.IFARIMA (may not be active yet)
Author:	Anita Sarkar [aut], Ankit Kumar Singh [aut], Md Yeasin [aut, cre], Ranjit Kumar Paul [aut], Amrit Kumar Paul [aut], Pushkar Bora [aut]
Maintainer:	Md Yeasin <yeasin.iasri at gmail.com>
License:	GPL-3
NeedsCompilation:	no
CRAN checks:	IFARIMA results

Documentation:

Reference manual:

IFARIMA.html , IFARIMA.pdf

Downloads:

Package source:	IFARIMA_0.1.0.tar.gz
Windows binaries:	r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries:	r-release (arm64): IFARIMA_0.1.0.tgz, r-oldrel (arm64): IFARIMA_0.1.0.tgz, r-release (x86_64): IFARIMA_0.1.0.tgz, r-oldrel (x86_64): IFARIMA_0.1.0.tgz

Linking:

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