Unified SPQR / SPQRX Model Fitting Interface

High-level wrapper for fitting either the SPQR or SPQRX model. This function selects the appropriate fitting routine based on the spqrx flag and optionally performs pre-training for the SPQRX model.

Usage

fit_spqrx(
  input_dim,
  hidden_dim,
  n.knots,
  x_training,
  x_validation,
  y_training,
  y_validation,
  hyperparameter = NULL,
  package.it = TRUE,
  pre_normalize = FALSE,
  spqrx = TRUE,
  pre_train = TRUE
)

Arguments

input_dim

Integer. Number of input covariates.

hidden_dim

Integer or vector. Hidden layer configuration.

n.knots

Integer. Number of spline knots.

x_training

Matrix or data frame of training covariates.

x_validation

Matrix or data frame of validation covariates.

y_training

Numeric vector of training responses.

y_validation

Numeric vector of validation responses.

hyperparameter

List of hyperparameters. If NULL, default values are generated via create.packages.hyperparameter().

package.it

Logical. Passed to lower-level fitting routines to determine whether the model should be returned as a packaged object. If false, passes back a trained keras object.

pre_normalize

Logical. Indicates whether prediction functions should assume pre-normalized inputs.

spqrx

Logical. If TRUE (default), fits the SPQRX model. If FALSE, fits the baseline SPQR model.

pre_train

Logical. If TRUE, performs pre-training when fitting the SPQRX model.

Value

A fitted SPQR or SPQRX model object, depending on the spqrx flag.