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BKTR: Bayesian Kernelized Tensor Regression
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.
Getting started
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Package details |
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| Author | Julien Lanthier [aut, cre, cph] (<https://orcid.org/0009-0008-8728-4996>), Mengying Lei [aut] (<https://orcid.org/0000-0001-7343-3323>), Aurélie Labbe [aut] (<https://orcid.org/0000-0002-4207-8143>), Lijun Sun [aut] (<https://orcid.org/0000-0001-9488-0712>) |
| Maintainer | Julien Lanthier <julien.lanthier@hec.ca> |
| License | MIT + file LICENSE |
| Version | 0.2.0 |
| Package repository | View on CRAN |
| Installation |
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