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BSCB 1.0.2

Changes

• Added Yang Han, Wei Liu, and Ian Hall as co-authors, reflecting their contributions to the methodology described in the accompanying paper (arXiv:2606.28015) as well as suggestions on optimize_function.R.

Features

• Implements six methods for constructing two-sided Bayesian simultaneous credible bands (BSCBs) for the regression curve in univariate polynomial regression over a finite covariate interval:
  • Conjugate Normal-Gamma priors, with empirical Bayes, unit-information, and g-prior hyperparameter specifications
  • Non-conjugate priors fitted via Hamiltonian Monte Carlo (HMC) using ‘cmdstanr’ (Normal-half-Normal and Normal-half-Cauchy priors)
  • A non-informative independent Jeffreys prior approach
• Provides functions for evaluating and comparing method performance:
  • ESCR() for computing the empirical simultaneous coverage rate
  • PSCP() for computing the posterior simultaneous coverage probability
• Includes a vignette demonstrating usage and comparing methods.

Documentation

• The methodology is described in Yang, F., Han, Y., Liu, W., & Hall, I. (2026), “Bayesian Simultaneous Credible Bands for Polynomial Regression.”

Bug fixes

• Fixed an issue where generate_simulation_data() with design_index = 2 (D-optimal design) could produce non-reproducible results even when seed was supplied. The underlying call to OptimalDesign::od_KL() previously relied on a time-based stopping rule (t.max), which made the number of completed restarts—and hence the result—dependent on machine speed. The search now stops after a fixed number of restarts (rest.max), ensuring full reproducibility given a fixed seed.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.