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-4.5-noble)EXPARMA_0.1.0.tar.gz(r-4.4-noble)
EXPARMA_0.1.0.tgz(r-4.4-emscripten)EXPARMA_0.1.0.tgz(r-4.3-emscripten)
EXPARMA.pdf |EXPARMA.html✨
EXPARMA/json (API)

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

Peer review:

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

1.00 score 162 downloads 4 exports 45 dependencies

Last updated 1 years agofrom:d94ac86352. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 02 2024
R-4.5-linuxOKNov 02 2024

Exports:BestExpEXPARMA_optimEXPARMAfitinit_val

Dependencies:clicolorspacecurlfansifarverforecastfracdiffgenericsggplot2gluegtableisobandjsonlitelabelinglatticelifecyclelmtestmagrittrMASSMatrixmgcvmunsellnlmennetpillarpkgconfigquadprogquantmodR6RColorBrewerRcppRcppArmadillorlangscalestibbletimeDatetseriesTTRurcautf8vctrsviridisLitewithrxtszoo