check_and_install       Function to check python environment and
                        install necessary packages
create_family           Function to create (custom) family
cv                      Generic cv function
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
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
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
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
prepare_data            Function to prepare data based on parsed
                        formulas
prepare_newdata         Function to prepare new data based on parsed
                        formulas
processor               Control function to define the processor for
                        terms in the formula
quant                   Generic quantile function
separate_define_relation
                        Function to define orthogonalization
                        connections in the formula
stddev                  Generic sd function
stop_iter_cv_result     Function to get the stoppting iteration from CV
subnetwork_init         Initializes a Subnetwork based on the Processed
                        Additive Predictor
tf_stride_cols          Function to index tensors columns
tfd_zinb                Implementation of a zero-inflated negbinom
                        distribution for TFP
tfd_zip                 Implementation of a zero-inflated poisson
                        distribution for TFP
