deepregression2.3.2 package

Function to check python environment and install necessary packages

Function to check if inputs are supported by corresponding fit functio...

Function to choose a kernel initializer for a torch layer

Method for extracting ensemble coefficient estimates

Character-to-parameter collection function needed for mixture of same ...

Function to combine two penalties

Convenience layer function

Function to create (custom) family

Function to create (custom) family

Function to create mgcv-type penalty

Generic cv function

Fitting Semi-Structured Deep Distributional Regression

Function to define output distribution based on dist_fun

Families for deepregression

Ensembling deepregression models

Generic deep ensemble function

Extract the smooth term from a deepregression term specification

Convenience function to extract penalty matrix and value

Extract variable from term

Character-tfd mapping function

Character-to-transformation mapping function

Character-to-transformation mapping function

Character-torch mapping function

Method for extracting the fitted values of an ensemble

Options for formula parsing

Formula helpers

Function to transform a distribution layer output into a loss function

Function to transform a distritbution layer output into a loss functio...

Function to define output distribution based on dist_fun

Define Predictor of a Deep Distributional Regression Model

Define Predictor of a Deep Distributional Regression Model

used by gam_processor

Function to return the fitted distribution

Obtain the conditional ensemble distribution

Extract gam part from wrapped term

Extract number in matching table of reduced gam term

Extract property of gamdata

Helper function to calculate amount of layers Needed when shared layer...

Function to return layer given model and name

Function to return layer number given model and name

Function to return layer numbers with trainable weights

Helper function to create an function that generates R6 instances of c...

Extract term names from the parsed formula content

Extract variables from wrapped node term

Extract attributes/hyper-parameters of the node term

Return partial effect of one smooth term

Extract processor name from term

Extract terms defined by specials in formula

Function to subset parsed formulas

Function to retrieve the weights of a structured layer

Function to return weight given model and name

Hadamard-type layers torch

Hadamard-type layers

Function to define smoothness and call mgcv's smooth constructor

Function to import required packages

Function to import required packages for tensorflow@import tensorflow ...

Function to import required packages for torch@import torch torchvisio...

Compile a Deep Distributional Regression Model

Function to create custom nn_linear module to overwrite reset_paramete...

Function to define a torch layer similar to a tf dense layer

NODE/ODTs Layer

Sparse Batch Normalization layer

Sparse 2D Convolutional layer

Function to define spline as Torch layer

Function to define spline as TensorFlow layer

Function to return the log_score

Function to loop through parsed formulas and apply data trafo

Generate folds for CV out of one hot encoded matrix

Make a DataGenerator from a data.frame or matrix

creates a generator for training

Convenience layer function

Function that takes term and create layer name

Generic functions for deepregression models

Function to initialize a nn_module Forward functions works with a list...

Function to define an optimizer combining multiple optimizers

Function to exclude NA values

Returns the parameter names for a given family

custom nn_linear module to overwrite reset_parameters # nn_init_consta...

Options for orthogonalization

Function to compute adjusted penalty when orthogonalizing

Orthogonalize a Semi-Structured Model Post-hoc

Orthogonalize structured term by another matrix

Options for penalty setup in the pre-processing

Pipe operator

Plot CV results from deepregression

Pre-calculate all gam parts from the list of formulas

Handler for prediction with gam terms

Generator function for deepregression objects

Function to additionally prepare data for fit process (torch)

Function to prepare data based on parsed formulas

Function to prepare input list for fit process, due to different appro...

Function to prepare new data based on parsed formulas

Prepares distributions for mixture process

Control function to define the processor for terms in the formula

Function that creates layer for each processor

Generic quantile function

random effect layer

Method to re-initialize weights of a "deepregression" model

Generic function to re-intialize model weights

Function to define orthogonalization connections in the formula

Generic sd function

Function to get the stoppting iteration from CV

Initializes a Subnetwork based on the Processed Additive Predictor

Initializes a Subnetwork based on the Processed Additive Predictor

TensorFlow repeat function which is not available for TF 2.0

Row-wise tensor product using TensorFlow

Split tensor in multiple parts

Function to index tensors columns

Function to index tensors last dimension

For using mean squared error via TFP

Implementation of a zero-inflated negbinom distribution for TFP

Implementation of a zero-inflated poisson distribution for TFP

Compile a Deep Distributional Regression Model (Torch)

Function to update miniconda and packages

Options for weights of layers