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:
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')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 years agofrom:19cb732d06. Checks:OK: 2. Indexed: yes.
Target | Result | Date |
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Doc / Vignettes | OK | Dec 18 2024 |
R-4.5-linux | OK | Dec 18 2024 |
Exports:ARIMAANN
Dependencies:clicolorspacecurlfansifarverforecastfracdiffgenericsggplot2gluegtableisobandjsonlitelabelinglatticelifecyclelmtestmagrittrMASSMatrixmgcvmunsellnlmennetpillarpkgconfigquadprogquantmodR6RColorBrewerRcppRcppArmadillorlangscalestibbletimeDatetseriesTTRurcautf8vctrsviridisLitewithrxtszoo
Readme and manuals
Help Manual
Help page | Topics |
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ARIMA-ANN hybrid model fitting | ARIMAANN |