Bayesian Unit Root Test for AR(1) Model with Trend Approximated by Linear Spline Function R package BayesSplineUR version 0.1.0 Performs Bayesian unit root testing for autoregressive time series models with non-linear trend components approximated by linear spline functions, as proposed by Kumar et al. (2020) <doi:10.19139/soic-2310-5070-786>. The package 'BayesSplineUR' computes posterior odds ratios, Bayes factors, and posterior probabilities for the unit root hypothesis against trend-stationary alternatives in models with linear spline trends or maintained polynomial trends as developed by Chaturvedi and Kumar (2005) <doi:10.1016/j.spl.2005.04.044>. Includes automatic knot selection using information criteria (AIC/BIC) and theoretical foundations for Bayesian unit root testing under structural breaks and maintained trends drawing from Schotman and van Dijk (1991) <doi:10.1016/0304-4076(91)90038-F>, Phillips and Perron (1988) <doi:10.1093/biomet/75.2.335>, Ouliaris et al. (1988) <doi:10.1007/978-94-009-2953-1_10>, and Perron (1989) <doi:10.2307/1913683>. Software Depends: R (>= 3.5.0) Imports: stats, graphics Suggests: knitr, rmarkdown, testthat (>= 3.0.0) Shikhar Tyagi <shikhar1093tyagi@gmail.com> Comprehensive R Archive Network (CRAN) Shikhar Tyagi [aut, cre] (ORCID: <https://orcid.org/0000-0003-1606-0844>), Arvind Pandey [aut], Bhupendra Singh [aut], Vrijesh Tripathi [aut] GPL (>= 3) 2026-08-06 application/tgz https://CRAN.R-project.org/package=BayesSplineUR doi:10.32614/CRAN.package.BayesSplineUR