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>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.0 |
rolling linux/jammy R-4.5 | TSANN_0.1.0.tar.gz |
18.0 KiB |
0.1.0 |
rolling linux/noble R-4.5 | TSANN_0.1.0.tar.gz |
17.8 KiB |
0.1.0 |
rolling source/ R- | TSANN_0.1.0.tar.gz |
2.4 KiB |
0.1.0 |
latest linux/jammy R-4.5 | TSANN_0.1.0.tar.gz |
18.0 KiB |
0.1.0 |
latest linux/noble R-4.5 | TSANN_0.1.0.tar.gz |
17.8 KiB |
0.1.0 |
latest source/ R- | TSANN_0.1.0.tar.gz |
2.4 KiB |
0.1.0 |
2026-04-26 source/ R- | TSANN_0.1.0.tar.gz |
2.4 KiB |
0.1.0 |
2026-04-23 source/ R- | TSANN_0.1.0.tar.gz |
2.4 KiB |
0.1.0 |
2026-04-09 windows/windows R-4.5 | TSANN_0.1.0.zip |
20.7 KiB |
0.1.0 |
2025-04-20 source/ R- | TSANN_0.1.0.tar.gz |
2.4 KiB |