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-4.5-any)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'))

On CRAN:

Conda:

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 8 scripts 162 downloads 2 exports 46 dependencies

Last updated 3 years agofrom:c326e242ea. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 12 2025
R-4.5-winOKMar 12 2025
R-4.5-macOKMar 12 2025
R-4.5-linuxOKMar 12 2025
R-4.4-winOKMar 12 2025
R-4.4-macOKMar 12 2025
R-4.4-linuxOKMar 12 2025
R-4.3-winOKMar 12 2025
R-4.3-macOKMar 12 2025

Exports:WaveletFittingWaveletFittingarma

Dependencies:clicolorspacecurlfansifarverforecastfracdiffgenericsggplot2gluegtableisobandjsonlitelabelinglatticelifecyclelmtestmagrittrMASSMatrixmgcvmunsellnlmennetpillarpkgconfigquadprogquantmodR6RColorBrewerRcppRcppArmadillorlangscalestibbletimeDatetseriesTTRurcautf8vctrsviridisLitewaveletswithrxtszoo