• Major update with expanded flexibility, improved diagnosis tools, and uncertainty quantification.
  • Additional distribution families: now supports poisson in addition to gaussian and binomial.
  • Per-term architecture configuration: hyperparameters (units, activation, learning rate, initializers, regularizers) can now be set per smooth term inside s().
  • Confidence Intervals (CI):
    • uncertainty_method argument allows estimation of epistemic uncertainty.
    • Intervals integrated into predict() and autoplot().
  • Cross-validation support: new validation_split parameter for monitoring validation losses during training.
  • Training diagnostics: new plot_history() function for visualizing training/validation loss curves per term and per backfitting iteration.
  • Improved summary(): displays per-term configuration, layer architectures, linear coefficients, and compact training history.
  • Diagnosis plots: new diagnose() function which provides a 2×2 diagnostic panel.
  • Autoplot enhancements: ggplot2-based diagnostic and effect plots with support for CI ribbons, per-term inspection, and factor vs continuous term visualization.
  • Testing: expanded test coverage for new families, CI estimation, plotting, and per-term configuration.
  • Internal refactoring:
    • Clean separation of deviance and link functions per family.
    • Consistent handling of sample weights.
    • Improved numerical stability (clamping in log/exp/probabilities).
  • verbose parameter is now used along all the required functions.

  • Tensorflow and Keras are now loaded when library(neuralGAM) is invoked for the first time, and therefore the first run of the neuralGAM() function has all the required packages ready.

  • Initial CRAN submission.