Bayesian Joint Circular Regression Using 'INLA' R package INLAcircular version 1.0.0 Provides a Bayesian regression framework for joint models with circular responses and covariates using integrated nested Laplace approximations, following Ye, Van Niekerk and Rue (2026) <doi:10.48550/arXiv.2602.08413>. The package supports link-adjusted von Mises likelihoods, shared latent predictors, structured latent effects, and optional LKJ-based multivariate covariance models. It also provides compiled circular densities and d/p/q/r penalized-complexity priors for von Mises, cardioid, and wrapped Cauchy concentration parameters as developed by Ye, Van Niekerk and Rue (2026) <doi:10.1177/1471082X261453677>. Software Depends: R (>= 4.1.0) Imports: dplyr, stats, utils Suggests: circular, graphpcor, INLA (>= 25.08.21), INLAtools, knitr, pkgload, rmarkdown Xiang Ye <xiang.ye@kaust.edu.sa> Comprehensive R Archive Network (CRAN) Xiang Ye [aut, cre, cph], Janet Van Niekerk [aut], Haavard Rue [aut, cph], Gerard Jungman [ctb, cph] (Bessel routines adapted from the GNU Scientific Library), Peter John Acklam [ctb] (Normal quantile approximation) GPL (>= 3) 2026-10-28 application/tgz https://CRAN.R-project.org/package=INLAcircular doi:10.32614/CRAN.package.INLAcircular