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

Package details

AuthorJulien 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>)
MaintainerJulien Lanthier <julien.lanthier@hec.ca>
LicenseMIT + file LICENSE
Package repositoryView on CRAN
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BKTR documentation built on Oct. 20, 2023, 5:07 p.m.