Man pages for EFAfactors
Determining the Number of Factors in Exploratory Factor Analysis
| af.softmax | An Activation Function: Softmax |
| CD | the Comparison Data (CD) Approach |
| CDF | the Comparison Data Forest (CDF) Approach |
| data.bfi | 25 Personality Items Representing 5 Factors |
| data.datasets | Subset Dataset for Training the Pre-Trained Deep Neural... |
| data.scaler | the Scaler for the Pre-Trained Deep Neural Network (DNN) |
| DNN_predictor | A Pre-Trained Deep Neural Network (DNN) for Determining the... |
| EFAhclust | Hierarchical Clustering for EFA |
| EFAindex | Various Indeces in EFA |
| EFAkmeans | K-means for EFA |
| EFAscreet | Scree Plot |
| EFAsim.data | Simulate Data that Conforms to the theory of Exploratory... |
| EFAvote | Voting Method for Number of Factors in EFA |
| EKC | Empirical Kaiser Criterion |
| extractor.feature.DNN | Extracting features for the Pre-Trained Deep Neural Network... |
| extractor.feature.FF | Extracting features According to Goretzko & Buhner (2020) |
| factor.analysis | Factor Analysis by Principal Axis Factoring |
| FF | Factor Forest (FF) Powered by An Tuned XGBoost Model for... |
| GenData | Simulating Data Following John Ruscio's RGenData |
| Hull | the Hull Approach |
| KGC | Kaiser-Guttman Criterion |
| load_DNN | Load the Trained Deep Neural Network (DNN) |
| load_scaler | Load the Scaler for the Pre-Trained Deep Neural Network (DNN) |
| load_xgb | Load the Tuned XGBoost Model |
| model.xgb | the Tuned XGBoost Model for Determining the Number of Facotrs |
| normalizor | Feature Normalization |
| PA | Parallel Analysis |
| plot.CD | Plot Comparison Data for Factor Analysis |
| plot.CDF | Plot Comparison Data Forest (CDF) Classification Probability... |
| plot.DNN_predictor | Plot DNN Predictor Classification Probability Distribution |
| plot.EFAhclust | Plot Hierarchical Cluster Analysis Dendrogram |
| plot.EFAkmeans | Plot EFA K-means Clustering Results |
| plot.EFAscreet | Plots the Scree Plot |
| plot.EFAvote | Plot Voting Results for Number of Factors |
| plot.EKC | Plot Empirical Kaiser Criterion (EKC) Plot |
| plot.FF | Plot Factor Forest (FF) Classification Probability... |
| plot.Hull | Plot Hull Plot for Factor Analysis |
| plot.KGC | Plot Kaiser-Guttman Criterion (KGC) Plot |
| plot.PA | Plot Parallel Analysis Scree Plot |
| predictLearner.classif.xgboost.earlystop | Prediction Function for the Tuned XGBoost Model with Early... |
| print.CD | Print Comparison Data Method Results |
| print.CDF | Print Comparison Data Forest (CDF) Results |
| print.DNN_predictor | Print DNN Predictor Method Results |
| print.EFAdata | Print the EFAsim.data |
| print.EFAhclust | Print EFAhclust Method Results |
| print.EFAkmeans | Print EFAkmeans Method Results |
| print.EFAscreet | Print the Scree Plot |
| print.EFAvote | Print Voting Method Results |
| print.EKC | Print Empirical Kaiser Criterion Results |
| print.FF | Print Factor Forest (FF) Results |
| print.Hull | Print Hull Method Results |
| print.KGC | Print Kaiser-Guttman Criterion Results |
| print.PA | Print Parallel Analysis Method Results |
