Expands the covariate matrix, adding interactions and polynomials. This is particularly useful for penalized regressions.
expand_df(X, int_order = 2, poly_order = 4, threshold = 0)Covariate matrix (no intercept).
Order of interactions to be added. Set equal to one if no interactions are desired.
Order of the polynomials to be added. Set equal to one if no polynomials are desired.
Drop binary variables representing less than threshold% of the population. Useful to speed up computation.
The expanded covariate matrix, as a data frame.
expand_df assumes that categorical variables are coded as factors. Also, no missing values are allowed.
expand_df uses model.matrix to expand factors to a set of dummy variables. Then, it identifies continuous covariates as those
not having 0 and 1 as unique values.
expand_df first introduces all the int_order-way interactions between the variables (using the expanded set of dummies), and then adds
poly_order-order polynomials for continuous covariates.