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varycoef  

Modeling Spatially Varying Coefficients
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("varycoef", "0.3.4")



Attach the package and use:
library("varycoef")
Maintained by
Jakob A. Dambon
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-10-11
Latest Update: 2022-09-17
Description:
Implements a maximum likelihood estimation (MLE) method for estimation and prediction of Gaussian process-based spatially varying coefficient (SVC) models (Dambon et al. (2021a) <doi:10.1016/j.spasta.2020.100470>).Covariance tapering (Furrer et al. (2006) <doi:10.1198/106186006X132178>) can be applied such that the method scales to large data. Further, it implements a joint variable selection of the fixed and random effects (Dambon et al. (2021b) <doi:10.1080/13658816.2022.2097684>). The package and its capabilities are described in (Dambon et al. (2021c) <doi:10.48550/arXiv.2106.02364>).
How to cite:
Jakob A. Dambon (2019). varycoef: Modeling Spatially Varying Coefficients. R package version 0.3.4, https://cran.r-project.org/web/packages/varycoef. Accessed 22 Dec. 2024.
Previous versions and publish date:
0.2.9 (2019-10-11 11:20), 0.2.10 (2020-02-21 18:50), 0.2.11 (2020-04-14 12:20), 0.2.12 (2020-07-18 15:30), 0.3.0 (2021-01-13 12:40), 0.3.1 (2021-06-03 15:00), 0.3.2 (2022-04-27 08:50), 0.3.3 (2022-06-01 01:50)
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