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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.

Version: 0.1.0
Imports: forecast, stats
Published: 2023-07-19
DOI: 10.32614/CRAN.package.EXPARMA
Author: Bishal Gurung [aut, cre], Saikat Das [aut], Achal Lama [aut], Kn Singh [aut]
Maintainer: Bishal Gurung <Bishal.Gurung at icar.gov.in>
License: GPL-3
NeedsCompilation: no
In views: TimeSeries
CRAN checks: EXPARMA results

Documentation:

Reference manual: EXPARMA.pdf

Downloads:

Package source: EXPARMA_0.1.0.tar.gz
Windows binaries: r-devel: EXPARMA_0.1.0.zip, r-release: EXPARMA_0.1.0.zip, r-oldrel: EXPARMA_0.1.0.zip
macOS binaries: r-release (arm64): EXPARMA_0.1.0.tgz, r-oldrel (arm64): EXPARMA_0.1.0.tgz, r-release (x86_64): EXPARMA_0.1.0.tgz, r-oldrel (x86_64): EXPARMA_0.1.0.tgz

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.