Changelog

Source: NEWS.md

SelectBoost.beta 0.4.5

• Added a pseudo-code vignette, refreshed the README with workflow details, and expanded the unit test suite for the new helpers.

• Fixed code and descriptions to get rid of notes during CRAN checks.

• Enabled optional parallel resampling in sb_beta()/sb_resample_groups() via future.apply, added S3 print/summary/autoplot helpers for sb_beta results, and documented the new behaviour in the README.

• Extended the stepwise beta selectors to handle observation weights and precision-submodel search, exposing precision coefficients in the returned paths.

• Added reproducible resampling caches and quality diagnostics to sb_resample_groups()/sb_beta(), including interval-response support that reuses pseudo-responses across correlation thresholds.

• Documented interval workflows more prominently by adding sb_beta_interval(), expanding the README/CRAN vignette guidance for selector choice and interval stability, and clarifying comparison-helper outputs and response squeezing.

SelectBoost.beta 0.4.4

• Add NEWS.md documenting development history.

SelectBoost.beta 0.4.3

• Added sb_beta() to run the full SelectBoost correlated-resampling loop with beta-regression selectors, plus a vignette illustrating the workflow.
• Added vignette section demonstrating the extended simulator and interval selection.

SelectBoost.beta 0.4.2

• New simulation_DATA() to generate interval-valued Beta-regression data:
  • interval = "jitter" (symmetric) or "quantile" (Beta quantile intervals).
  • Works with fastboost_interval(); added a small vignette and unit test.
  • Supports mixed mechanisms (row-wise jitter vs quantile), asymmetric jitter widths (delta_low/delta_high), asymmetric quantile coverage (alpha_low/alpha_high), covariate-driven parameters (accept functions of (mu, X)), and optional missing bounds per row (na_rate, na_side).

SelectBoost.beta 0.4.1

• Comparison helpers and visualizations:
  • compare_selectors_single(), compare_selectors_bootstrap() to run all selectors (AIC/BIC/AICc, GAMLSS LASSO/ENet*, GLMNET) and compute selection frequencies.
  • plot_compare_coeff(), plot_compare_freq() heatmaps to compare selectors side by side.
  • Vignette expanded to include simulated data and two real-ish datasets after scaling to (0,1).
• Kept fastboost_interval() (interval response stability selection), C++ IRLS speedups, and prestandardize option for betareg_glmnet().
  • ENet requires gamlss.lasso if installed.

SelectBoost.beta 0.4.0

• Initial beta-regression integration for SelectBoost:
  • Stepwise AIC, BIC, and AICc wrappers around betareg.
  • GAMLSS LASSO (gamlss::ri) and optional Elastic-Net (gamlss.lasso::gnet).
  • Pure glmnet (IRLS + weighted Gaussian ENet) with optional prestandardize.
  • fastboost_interval() prototype for interval responses.
  • First vignette + roxygenized docs.