Package: EXPARMA 0.1.0

Bishal Gurung

EXPARMA: Fitting of Exponential Autoregressive Moving Average (EXPARMA) Model

The amplitude-dependent autoregressive time series model (EXPAR) proposed by Haggan and Ozaki (1981) <doi:10.2307/2335819> was improved by incorporating the moving average (MA) framework for capturing the variability efficiently. Parameters of the EXPARMA model can be estimated using this package. The user is provided with the best fitted EXPARMA model for the data set under consideration.

Authors:Bishal Gurung [aut, cre], Saikat Das [aut], Achal Lama [aut], Kn Singh [aut]

EXPARMA_0.1.0.tar.gz
EXPARMA_0.1.0.tar.gz(r-4.7-any)EXPARMA_0.1.0.tar.gz(r-4.6-any)
EXPARMA_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
EXPARMA/json (API)

# Install 'EXPARMA' in R:
install.packages('EXPARMA', 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 218 downloads 4 exports 31 dependencies

Last updated from:d94ac86352. Checks:4 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK108
source / vignettesOK182
linux-release-x86_64OK107
wasm-releaseOK103

Exports:BestExpEXPARMA_optimEXPARMAfitinit_val

Dependencies:clicolorspacecpp11farverforecastfracdiffgenericsggplot2gluegtableisobandlabelinglatticelifecyclelmtestmagrittrnlmennetR6RColorBrewerRcppRcppArmadillorlangS7scalestimeDateurcavctrsviridisLitewithrzoo