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 |