![[R logo]](../../../doc/html/Rlogo.svg)
![[Up]](../../../doc/html/left.jpg)
![[Top]](../../../doc/html/up.jpg)
| check_and_install | Function to check python environment and install necessary packages |
| coef.deepregression | Generic functions for deepregression models |
| create_family | Function to create (custom) family |
| cv | Generic cv function |
| cv.deepregression | Generic functions for deepregression models |
| deepregression | Fitting Semi-Structured Deep Distributional Regression |
| distfun_to_dist | Function to define output distribution based on dist_fun |
| extractval | Extract value in term name |
| family_to_tfd | Character-tfd mapping function |
| family_to_trafo | Character-to-transformation mapping function |
| fit | Generic train function |
| fit.deepregression | Generic functions for deepregression models |
| fitted.deepregression | Generic functions for deepregression models |
| from_dist_to_loss | Function to transform a distritbution layer output into a loss function |
| from_preds_to_dist | Define Predictor of a Deep Distributional Regression Model |
| get_distribution | Function to return the fitted distribution |
| get_partial_effect | Return partial effect of one smooth term |
| get_type_pfc | Function to subset parsed formulas |
| get_weight_by_name | Function to retrieve the weights of a structured layer |
| handle_gam_term | Function to define smoothness and call mgcv's smooth constructor |
| keras_dr | Compile a Deep Distributional Regression Model |
| layer_add_identity | Convenience layer function |
| layer_concatenate_identity | Convenience layer function |
| log_score | Function to return the log_score |
| loop_through_pfc_and_call_trafo | Function to loop through parsed formulas and apply data trafo |
| makeInputs | Convenience layer function |
| make_folds | Generate folds for CV out of one hot encoded matrix |
| make_generator | creates a generator for training |
| make_generator_from_matrix | Make a DataGenerator from a data.frame or matrix |
| make_tfd_dist | Families for deepregression |
| mean.deepregression | Generic functions for deepregression models |
| names_families | Returns the parameter names for a given family |
| orthog_control | Options for orthogonalization |
| penalty_control | Options for penalty setup in the pre-processing |
| plot.deepregression | Generic functions for deepregression models |
| plot_cv | Plot CV results from deepregression |
| predict.deepregression | Generic functions for deepregression models |
| prepare_data | Function to prepare data based on parsed formulas |
| prepare_newdata | Function to prepare new data based on parsed formulas |
| print.deepregression | Generic functions for deepregression models |
| processor | Control function to define the processor for terms in the formula |
| quant | Generic quantile function |
| quant.deepregression | Generic functions for deepregression models |
| separate_define_relation | Function to define orthogonalization connections in the formula |
| stddev | Generic sd function |
| stddev.deepregression | Generic functions for deepregression models |
| stop_iter_cv_result | Function to get the stoppting iteration from CV |
| subnetwork_init | Initializes a Subnetwork based on the Processed Additive Predictor |
| tfd_zinb | Implementation of a zero-inflated negbinom distribution for TFP |
| tfd_zip | Implementation of a zero-inflated poisson distribution for TFP |
| tf_stride_cols | Function to index tensors columns |