Bayesian Kernelized Tensor Regression R package BKTR version 0.2.0 Facilitates scalable spatiotemporally varying coefficient modelling with Bayesian kernelized tensor regression. The important features of this package are: (a) Enabling local temporal and spatial modeling of the relationship between the response variable and covariates. (b) Implementing the model described by Lei et al. (2023) <doi:10.48550/arXiv.2109.00046>. (c) Using a Bayesian Markov Chain Monte Carlo (MCMC) algorithm to sample from the posterior distribution of the model parameters. (d) Employing a tensor decomposition to reduce the number of estimated parameters. (e) Accelerating tensor operations and enabling graphics processing unit (GPU) acceleration with the 'torch' package. Software Depends: R (>= 4.0.0) Imports: torch (>= 0.13.0), R6, R6P, ggplot2, ggmap, data.table Suggests: knitr, rmarkdown, R.rsp Julien Lanthier <julien.lanthier@hec.ca> Comprehensive R Archive Network (CRAN) Julien Lanthier [aut, cre, cph] (ORCID: <https://orcid.org/0009-0008-8728-4996>), Mengying Lei [aut] (ORCID: <https://orcid.org/0000-0001-7343-3323>), Aurélie Labbe [aut] (ORCID: <https://orcid.org/0000-0002-4207-8143>), Lijun Sun [aut] (ORCID: <https://orcid.org/0000-0001-9488-0712>) MIT + file LICENSE (https://CRAN.R-project.org/package=BKTR/LICENSE) 2024-08-18 application/tgz https://CRAN.R-project.org/package=BKTR doi:10.32614/CRAN.package.BKTR