Changes in version 0.5.0 - Add circular_regression() as the main fixed-effect modeling interface. - Add angular_two_step() as an explicit consensus-then-homogeneous workflow. - Add S3 methods for coefficients, fitted values, residuals, predictions, summaries, plots, log-likelihoods and information criteria. - Improve consensus numerical stability for large Bessel-function arguments. - Add validation for finite angles, non-negative modifiers, weights, controls and initial values. - Align logLik.consensus(), AIC.consensus() and BIC.consensus() with the full von Mises log-likelihood by including the normalizing constant. This changes absolute consensus likelihood and information-criterion values but does not change the fitted estimates. - Add summary.angular_re() and print.summary.angular_re(). - Preserve model-frame na.action information in angular() objects. - Replace the draft overview vignette with two reproducible HTML vignettes. - Add pkgdown configuration and a workflow diagnostics article. - Add a package-data workflow vignette for R Journal reviewer support. - Add a minimal GitHub Actions R CMD check workflow. - Clarify random-effects and special-wrapper documentation. - Clarify documented provenance for noshiro and the remaining provenance limitations for multiplebison. - Add a related scientific reference for the multiplebison study context. - Expand tests for simulation recovery, predictions, NA handling, weights, modulo invariance and small-sample fits. Changes in version 0.4.0 - See CHANGELOG_0.4.0.md in the development repository for development notes. That file is not included in the CRAN build. Changes in version 0.1.1 - Improve stability of angular and consensus estimators with QR-based updates and better handling of reference-only models. - Implement observation weights in consensus() and remove the deprecated model argument across the API. - Make angular_re() usable without workarounds, add Hessian conditioning checks, and provide more robust predictions. - Refresh documentation and vignette examples, and add an automated test suite covering key model features.