R Packages for Differential Step Functioning: A Comprehensive List

Here is a comprehensive list of R packages that can be used for calculating differential step functioning:

1. 'stepR': Provides functions for stepwise regression and stepwise model selection.
2. 'leaps': Implements the leaps-and-bounds algorithm for exhaustive search of regression models.
3. 'MASS': Contains functions for stepwise model selection, including stepAIC.
4. 'glmnet': Implements Lasso and Elastic-Net regularization methods for linear and logistic regression.
5. 'caret': Contains the stepwise variable selection function varImp.
6. 'Boruta': Implements the Boruta algorithm for feature selection in machine learning.
7. 'mboost': Implements boosting algorithms for regression and classification, including stepwise model selection.
8. 'rms': Contains functions for forward and backward stepwise model selection.
9. 'MuMIn': Implements model selection techniques, including stepwise regression.
10. 'adespatial': Contains functions for stepwise model selection in spatial analysis.