Package: IFARIMA 0.1.0

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.zip(r-4.5-any)
IFARIMA_0.1.0.tgz(r-4.6-any)IFARIMA_0.1.0.tgz(r-4.5-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://yeasinstat.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 59 downloads 1 exports 31 dependencies

Last updated from:02d8f258bf. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK144
source / vignettesOK169
linux-releaseOK151
macos-releaseOK119
macos-oldrelOK105
windows-develOK63
windows-releaseOK80
windows-oldrelOK62
wasm-releaseOK94

Exports:IFARIMA

Dependencies:clicolorspacecpp11farverforecastfracdiffgenericsggplot2gluegtableisobandlabelinglatticelifecyclelmtestmagrittrnlmennetR6RColorBrewerRcppRcppArmadillorlangS7scalestimeDateurcavctrsviridisLitewithrzoo