check_and_install       Function to check python environment and
                        install necessary packages
coef.drEnsemble         Method for extracting ensemble coefficient
                        estimates
combine_penalties       Function to combine two penalties
create_family           Function to create (custom) family
create_penalty          Function to create mgcv-type penalty
cv                      Generic cv function
deepregression          Fitting Semi-Structured Deep Distributional
                        Regression
distfun_to_dist         Function to define output distribution based on
                        dist_fun
ensemble                Generic deep ensemble function
ensemble.deepregression
                        Ensemblind deepregression models
extract_S               Convenience function to extract penalty matrix
                        and value
extract_pure_gam_part   Extract the smooth term from a deepregression
                        term specification
extractval              Formula helpers
extractvar              Extract variable from term
family_to_tfd           Character-tfd mapping function
family_to_trafo         Character-to-transformation mapping function
fitted.drEnsemble       Method for extracting the fitted values of an
                        ensemble
form_control            Options for formula parsing
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
gam_plot_data           used by gam_processor
get_distribution        Function to return the fitted distribution
get_ensemble_distribution
                        Obtain the conditional ensemble distribution
get_gam_part            Extract gam part from wrapped term
get_gamdata             Extract property of gamdata
get_gamdata_reduced_nr
                        Extract number in matching table of reduced gam
                        term
get_layer_by_opname     Function to return layer given model and name
get_layernr_by_opname   Function to return layer number given model and
                        name
get_layernr_trainable   Function to return layer numbers with trainable
                        weights
get_names_pfc           Extract term names from the parsed formula
                        content
get_partial_effect      Return partial effect of one smooth term
get_processor_name      Extract processor name from term
get_special             Extract terms defined by specials in formula
get_type_pfc            Function to subset parsed formulas
get_weight_by_name      Function to retrieve the weights of a
                        structured layer
get_weight_by_opname    Function to return weight given model and name
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_generator         Function that creates layer for each processor
layer_sparse_conv_2d    Sparse 2D Convolutional layer
layer_spline            Function to define spline as TensorFlow layer
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
makelayername           Function that takes term and create layer name
multioptimizer          Function to define an optimizer combining
                        multiple optimizers
names_families          Returns the parameter names for a given family
orthog_P                Function to compute adjusted penalty when
                        orthogonalizing
orthog_control          Options for orthogonalization
orthog_post_fitting     Orthogonalize a Semi-Structured Model Post-hoc
orthog_structured_smooths_Z
                        Orthogonalize structured term by another matrix
penalty_control         Options for penalty setup in the pre-processing
plot.deepregression     Generic functions for deepregression models
plot_cv                 Plot CV results from deepregression
precalc_gam             Pre-calculate all gam parts from the list of
                        formulas
predict_gen             Generator function for deepregression objects
prepare_data            Function to prepare data based on parsed
                        formulas
prepare_newdata         Function to prepare new data based on parsed
                        formulas
process_terms           Control function to define the processor for
                        terms in the formula
quant                   Generic quantile function
reinit_weights          Genereic function to re-intialize model weights
reinit_weights.deepregression
                        Method to re-initialize weights of a
                        '"deepregression"' model
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_repeat               TensorFlow repeat function which is not
                        available for TF 2.0
tf_row_tensor           Row-wise tensor product using TensorFlow
tf_split_multiple       Split tensor in multiple parts
tf_stride_cols          Function to index tensors columns
tf_stride_last_dim_tensor
                        Function to index tensors last dimension
tfd_mse                 For using mean squared error via TFP
tfd_zinb                Implementation of a zero-inflated negbinom
                        distribution for TFP
tfd_zip                 Implementation of a zero-inflated poisson
                        distribution for TFP
tib_layer               Hadamard-type layers
update_miniconda_deepregression
                        Function to update miniconda and packages
weight_control          Options for weights of layers
