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.zip(r-4.7-any)EXPARMA_0.1.0.zip(r-4.6-any)
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✨
DESCRIPTION
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 346 downloads 4 exports 31 dependencies

Last updated from:d94ac86352. Checks:6 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK95
source / vignettesOK271
linux-releaseOK96
windows-develOK57
windows-releaseOK53
wasm-releaseOK86

Exports:BestExpEXPARMA_optimEXPARMAfitinit_val

Dependencies:clicolorspacecpp11farverforecastfracdiffgenericsggplot2gluegtableisobandlabelinglatticelifecyclelmtestmagrittrnlmennetR6RColorBrewerRcppRcppArmadillorlangS7scalestimeDateurcavctrsviridisLitewithrzoo