print.LSTM

This function prints the number of factors suggested by the 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.

Haijiang Qin

LSTMfactors

Determining the Number of Factors in Exploratory Factor Analysis
by LSTM

Lei Guo

print.LSTM function

<dl><dt>x</dt>
<dd>An object of class <code>LSTM</code>, representing the results to be printed.</dd>
<dt>...</dt>
<dd>Additional arguments to be passed to the plotting function.</dd></dl>

Arguments

Print LSTM Results — print.LSTM

<dl>

<dt>x</dt>
<dd>An object of class <code>LSTM</code>, representing the results to be printed.</dd>


<dt>...</dt>
<dd>Additional arguments to be passed to the plotting function.</dd>

</dl>

print.LSTM: Print LSTM Results

Description

Usage

Value

Arguments

See Also