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stgam
View on CRAN: Click
here
Download and install stgam package within the R console
Install from CRAN:
install.packages("stgam")
Install from Github:
library("remotes")
install_github("cran/stgam")
Install by package version:
library("remotes")
install_version("stgam", "0.0.1.2")
Attach the package and use:
library("stgam")
Maintained by
Lex Comber
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.stgam . https://github.com/lexcomber/stgam/issues . https://github.com/lexcomber/stgam . stgam results . stgam.pdf . Introduction to space-time GAMS with 'stgam' . Determining Space-Time model form and Bayesian Model Avergaing (BMA) with 'stgam' . stgam_0.0.1.2.tar.gz . stgam_0.0.1.2.zip . stgam_0.0.1.2.zip . stgam_0.0.1.2.zip . stgam_0.0.1.2.tgz . stgam_0.0.1.2.tgz . stgam_0.0.1.2.tgz . stgam_0.0.1.2.tgz . stgam_0.0.1.2.tgz . stgam_0.0.1.2.tgz . stgam archive . https://CRAN.R-project.org/package=stgam .
First Published: 2024-06-25
Latest Update: 2024-06-25
Description:
A framework for specifying spatially, temporally and spatial-and-temporally varying coefficient models using Generalized Additive Models with Gaussian Process smooths. The smooths are parameterised with location and / or time attributes. Importantly the framework supports the investigation of the presence and nature of any space-time dependencies in the data, allows the user to evaluate different model forms (specifications) and to pick the most probable model or to combine multiple varying coefficient models using Bayesian Model Averaging. For more details see: Brunsdon et al (2023) <doi:10.4230/LIPIcs.GIScience.2023.17>, Comber et al (2023) <doi:10.4230/LIPIcs.GIScience.2023.22> and Comber et al (2024) <doi:10.1080/13658816.2023.2270285>.
How to cite:
Lex Comber (2024). stgam: Spatially and Temporally Varying Coefficient Models Using Generalized Additive Models. R package version 0.0.1.2, https://cran.r-project.org/web/packages/stgam. Accessed 04 Apr. 2025.
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