MAP method.STOC method.LSTM, implemented through NN.LSTM data.datasets.LSTM and the normalizing scale data.scaler.LSTM.load.scaler and load.NN to extract data and models from different neural networks, and removed load_scaler and load_DNN.DNN data.datasets and the normalizing scale data.scaler to data.datasets.DNN and data.scaler.DNN.DNN_predictor into NN, enabling it to use different neural network models for factor retention.extractor.feature.FNN into extractor.feature.NN, enabling it to extract features for different neural network models.. globally instead of the underscore _.CD used summation. Although this did not affect the significance test, it has been updated to use the mean to align perfectly with the theoretical formulation.print and plot.factor.analysis in version 1.2.3, methods involving factor.analysis may produce different outputs compared to versions prior to 1.2.3, such as CD and FF. Please take the results from the new version as the standard.factor.analysis only returned nfact eigenvalues.Examples have been removed to avoid excessive time consumption during automatic checks.factor.analysis may be inverted.CDF function code to improve its execution efficiency.GenData when the number of questions is very large.src/Makevars to achieve better portability.ParamHelpers, has been rewritten based on version 1.14.1 to support the FF function and no longer depends on the R package ParamHelpers.EFAsim.data no longer requires the parameter seed.check_python_libraries has been provided to help users check if the Python libraries numpy and onnxruntime are missing, and users can easily install them using this function when they are not present.Hull.DESCRIPTION field.