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BKTR  

Bayesian Kernelized Tensor Regression
View on CRAN: Click here


Download and install BKTR package within the R console
Install from CRAN:
install.packages("BKTR")

Install from Github:
library("remotes")
install_github("cran/BKTR")

Install by package version:
library("remotes")
install_version("BKTR", "0.2.0")



Attach the package and use:
library("BKTR")
Maintained by
Julien Lanthier
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-10-20
Latest Update: 2024-08-18
Description:
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) . (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.
How to cite:
Julien Lanthier (2023). BKTR: Bayesian Kernelized Tensor Regression. R package version 0.2.0, https://cran.r-project.org/web/packages/BKTR. Accessed 05 Jun. 2026.
Previous versions and publish date:
0.1.1 (2023-10-20 13:50)
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Complete documentation for BKTR
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