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.
Version: 0.2.0 Depends: R (≥ 4.0.0) Imports: torch (≥ 0.13.0), R6, R6P, ggplot2, ggmap, data.table Suggests: knitr, rmarkdown, R.rsp Published: 2024-08-18 DOI: 10.32614/CRAN.package.BKTR Author: Julien Lanthier [aut, cre, cph], Mengying Lei [aut], Aurélie Labbe [aut], Lijun Sun [aut] Maintainer: Julien Lanthier <julien.lanthier at hec.ca> BugReports: https://github.com/julien-hec/BKTR/issues License: MIT + file LICENSE NeedsCompilation: no Materials: README, NEWS CRAN checks: BKTR results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=BKTR to link to this page.
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