Package: IFARIMA 0.1.0

Md Yeasin

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>.

Authors:Anita Sarkar [aut], Ankit Kumar Singh [aut], Md Yeasin [aut, cre], Ranjit Kumar Paul [aut], Amrit Kumar Paul [aut], Pushkar Bora [aut]

IFARIMA_0.1.0.tar.gz
IFARIMA_0.1.0.zip(r-4.7-any)IFARIMA_0.1.0.zip(r-4.6-any)
IFARIMA_0.1.0.tar.gz(r-4.7-any)IFARIMA_0.1.0.tar.gz(r-4.6-any)
IFARIMA_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
IFARIMA/json (API)

# Install 'IFARIMA' in R:
install.packages('IFARIMA', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 1 exports 31 dependencies

Last updated from:02d8f258bf. Checks:6 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK120
source / vignettesOK177
linux-releaseOK112
windows-develOK72
windows-releaseOK70
wasm-releaseOK92

Exports:IFARIMA

Dependencies:clicolorspacecpp11farverforecastfracdiffgenericsggplot2gluegtableisobandlabelinglatticelifecyclelmtestmagrittrnlmennetR6RColorBrewerRcppRcppArmadillorlangS7scalestimeDateurcavctrsviridisLitewithrzoo