Package: WaveletArima 0.1.2

WaveletArima: Wavelet-ARIMA Model for Time Series Forecasting

Noise in the time-series data significantly affects the accuracy of the ARIMA model. Wavelet transformation decomposes the time series data into subcomponents to reduce the noise and help to improve the model performance. The wavelet-ARIMA model can achieve higher prediction accuracy than the traditional ARIMA model. This package provides Wavelet-ARIMA model for time series forecasting based on the algorithm by Aminghafari and Poggi (2012) and Paul and Anjoy (2018) <doi:10.1142/S0219691307002002> <doi:10.1007/s00704-017-2271-x>.

Authors:Dr. Ranjit Kumar Paul [aut, cre], Mr. Sandipan Samanta [aut], Dr. Md Yeasin [aut]

WaveletArima_0.1.2.tar.gz
WaveletArima_0.1.2.zip(r-4.5)WaveletArima_0.1.2.zip(r-4.4)WaveletArima_0.1.2.zip(r-4.3)
WaveletArima_0.1.2.tgz(r-4.4-any)WaveletArima_0.1.2.tgz(r-4.3-any)
WaveletArima_0.1.2.tar.gz(r-4.5-noble)WaveletArima_0.1.2.tar.gz(r-4.4-noble)
WaveletArima_0.1.2.tgz(r-4.4-emscripten)WaveletArima_0.1.2.tgz(r-4.3-emscripten)
WaveletArima.pdf |WaveletArima.html
WaveletArima/json (API)

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

Peer review:

On CRAN:

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

1.48 score 1 packages 7 scripts 159 downloads 2 exports 46 dependencies

Last updated 2 years agofrom:c326e242ea. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 13 2024
R-4.5-winOKOct 13 2024
R-4.5-linuxOKOct 13 2024
R-4.4-winOKOct 13 2024
R-4.4-macOKOct 13 2024
R-4.3-winOKOct 13 2024
R-4.3-macOKOct 13 2024

Exports:WaveletFittingWaveletFittingarma

Dependencies:clicolorspacecurlfansifarverforecastfracdiffgenericsggplot2gluegtableisobandjsonlitelabelinglatticelifecyclelmtestmagrittrMASSMatrixmgcvmunsellnlmennetpillarpkgconfigquadprogquantmodR6RColorBrewerRcppRcppArmadillorlangscalestibbletimeDatetseriesTTRurcautf8vctrsviridisLitewaveletswithrxtszoo