autoann
Neural Network–Based Model Selection and Forecasting
Description
Provides a systematic framework for neural network–based model selection and forecasting using single hidden layer feed-forward networks. It evaluates all possible combinations of predictor variables and hidden layer configurations, selecting the optimal model based on predictive accuracy criteria such as root mean squared error (RMSE) and mean absolute percentage error (MAPE). Predictors are automatically standardized, and model performance is assessed using out-of-sample validation. The package is designed for empirical modelling and forecasting in economics, agriculture, trade, climate, and related applied research domains where nonlinear relationships and robust predictive performance are of primary interest.
Downloads
33.3K
Last 30 days
626th
57.3K
Last 90 days
58.8K
Last year
Trend: +41.7% (30d vs prior 30d)
9
Last 30 days
25
Last 90 days
43
Last year
Trend: -25% (30d vs prior 30d)
5
Last 7 days
22
Last 30 days
0
All-time
autoCRAN-only: this name is served only by autoCRAN, so the count is exact.
CRAN Check Status
Show all 13 flavors
| Flavor | Status |
|---|---|
| r-devel-linux-x86_64-debian-clang | OK |
| r-devel-linux-x86_64-debian-gcc | OK |
| r-devel-linux-x86_64-fedora-clang | OK |
| r-devel-linux-x86_64-fedora-gcc | OK |
| r-devel-windows-x86_64 | OK |
| r-oldrel-macos-arm64 | OK |
| r-oldrel-macos-x86_64 | OK |
| r-oldrel-windows-x86_64 | OK |
| r-patched-linux-x86_64 | OK |
| r-release-linux-x86_64 | OK |
| r-release-macos-arm64 | OK |
| r-release-macos-x86_64 | OK |
| r-release-windows-x86_64 | OK |
Check History
OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026
Dependency Network
Version History
1 trackedR Observatory began tracking this package on Mar 10, 2026; it first appeared on CRAN Jan 15, 2026. Releases before tracking aren’t shown.