LSTMfactors
Determining the Number of Factors in Exploratory Factor Analysis by LSTM
A method for factor retention using a pre-trained Long Short Term Memory (LSTM) Network, which is originally developed by Hochreiter and Schmidhuber (1997) <doi:10.1162/neco.1997.9.8.1735>, is provided. The sample size of the dataset used to train the LSTM model is 1,000,000. Each sample is a batch of simulated response data with a specific latent factor structure. The eigenvalues of these response data will be used as sequential data to train the LSTM. The pre-trained LSTM is capable of factor retention for real response data with a true latent factor number ranging from 1 to 10, that is, determining the number of factors.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0.0 |
rolling linux/jammy R-4.5 | LSTMfactors_1.0.0.tar.gz |
289.1 KiB |
1.0.0 |
rolling linux/noble R-4.5 | LSTMfactors_1.0.0.tar.gz |
289.0 KiB |
1.0.0 |
rolling source/ R- | LSTMfactors_1.0.0.tar.gz |
256.7 KiB |
1.0.0 |
latest linux/jammy R-4.5 | LSTMfactors_1.0.0.tar.gz |
289.1 KiB |
1.0.0 |
latest linux/noble R-4.5 | LSTMfactors_1.0.0.tar.gz |
289.0 KiB |
1.0.0 |
latest source/ R- | LSTMfactors_1.0.0.tar.gz |
256.7 KiB |
1.0.0 |
2026-04-26 source/ R- | LSTMfactors_1.0.0.tar.gz |
256.7 KiB |
1.0.0 |
2026-04-23 source/ R- | LSTMfactors_1.0.0.tar.gz |
256.7 KiB |
1.0.0 |
2026-04-09 windows/windows R-4.5 | LSTMfactors_1.0.0.zip |
292.3 KiB |