Package: ARIMAANN 0.1.0

Mrinmoy Ray

ARIMAANN: Time Series Forecasting using ARIMA-ANN Hybrid Model

Testing, Implementation, and Forecasting of the ARIMA-ANN hybrid model. The ARIMA-ANN hybrid model combines the distinct strengths of the Auto-Regressive Integrated Moving Average (ARIMA) model and the Artificial Neural Network (ANN) model for time series forecasting.For method details see Zhang, GP (2003) <doi:10.1016/S0925-2312(01)00702-0>.

Authors:Ramasubramanian V. [aut, ctb], Mrinmoy Ray [aut, cre]

ARIMAANN_0.1.0.tar.gz
ARIMAANN_0.1.0.tar.gz(r-4.5-noble)ARIMAANN_0.1.0.tar.gz(r-4.4-noble)
ARIMAANN_0.1.0.tgz(r-4.4-emscripten)ARIMAANN_0.1.0.tgz(r-4.3-emscripten)
ARIMAANN.pdf |ARIMAANN.html✨
ARIMAANN/json (API)

# Install 'ARIMAANN' in R:
install.packages('ARIMAANN', 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.

1.30 score 2 stars 316 downloads 1 exports 45 dependencies

Last updated 2 years agofrom:19cb732d06. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 18 2024
R-4.5-linuxOKNov 18 2024

Exports:ARIMAANN

Dependencies:clicolorspacecurlfansifarverforecastfracdiffgenericsggplot2gluegtableisobandjsonlitelabelinglatticelifecyclelmtestmagrittrMASSMatrixmgcvmunsellnlmennetpillarpkgconfigquadprogquantmodR6RColorBrewerRcppRcppArmadillorlangscalestibbletimeDatetseriesTTRurcautf8vctrsviridisLitewithrxtszoo