Package: TSANN 0.1.0
TSANN: Time Series Artificial Neural Network
The best ANN structure for time series data analysis is a demanding need in the present era. This package will find the best-fitted ANN model based on forecasting accuracy. The optimum size of the hidden layers was also determined after determining the number of lags to be included. This package has been developed using the algorithm of Paul and Garai (2021) <doi:10.1007/s00500-021-06087-4>.
Authors:
TSANN_0.1.0.tar.gz
TSANN_0.1.0.zip(r-4.5)TSANN_0.1.0.zip(r-4.4)TSANN_0.1.0.zip(r-4.3)
TSANN_0.1.0.tgz(r-4.4-any)TSANN_0.1.0.tgz(r-4.3-any)
TSANN_0.1.0.tar.gz(r-4.5-noble)TSANN_0.1.0.tar.gz(r-4.4-noble)
TSANN_0.1.0.tgz(r-4.4-emscripten)TSANN_0.1.0.tgz(r-4.3-emscripten)
TSANN.pdf |TSANN.html✨
TSANN/json (API)
# Install 'TSANN' in R: |
install.packages('TSANN', repos = c('https://yeasinstat.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 3 years agofrom:4b20978c3a. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 08 2024 |
R-4.5-win | OK | Nov 08 2024 |
R-4.5-linux | OK | Nov 08 2024 |
R-4.4-win | OK | Nov 08 2024 |
R-4.4-mac | OK | Nov 08 2024 |
R-4.3-win | OK | Nov 08 2024 |
R-4.3-mac | OK | Nov 08 2024 |
Exports:Auto.TSANN
Dependencies:clicolorspacecurlfansifarverforecastfracdiffgenericsggplot2gluegtablegtoolsisobandjsonlitelabelinglatticelifecyclelmtestmagrittrMASSMatrixmgcvmunsellnlmennetpillarpkgconfigquadprogquantmodR6RColorBrewerRcppRcppArmadillorlangscalestibbletimeDatetseriesTTRurcautf8vctrsviridisLitewithrxtszoo
Readme and manuals
Help Manual
Help page | Topics |
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Time Series Artificial Neural Network | Auto.TSANN |