Package: stgam 0.0.1.3

stgam: Spatially and Temporally Varying Coefficient Models Using Generalized Additive Models

A framework for specifying spatially, temporally and spatially-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>, Comber et al (2004) <doi:10.3390/ijgi13120459>.

Authors:Lex Comber [aut, cre], Paul Harris [ctb], Chris Brunsdon [ctb]

stgam_0.0.1.3.tar.gz
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stgam_0.0.1.3.tgz(r-4.5-any)stgam_0.0.1.3.tgz(r-4.4-any)stgam_0.0.1.3.tgz(r-4.3-any)
stgam_0.0.1.3.tar.gz(r-4.5-noble)stgam_0.0.1.3.tar.gz(r-4.4-noble)
stgam_0.0.1.3.tgz(r-4.4-emscripten)stgam_0.0.1.3.tgz(r-4.3-emscripten)
stgam.pdf |stgam.html
stgam/json (API)
NEWS

# Install 'stgam' in R:
install.packages('stgam', repos = c('https://lexcomber.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/lexcomber/stgam/issues

Datasets:

On CRAN:

Conda:

5.30 score 2 stars 9 scripts 202 downloads 6 exports 65 dependencies

Last updated 3 months agofrom:d99d7469c8. Checks:6 OK, 3 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 04 2025
R-4.5-winNOTEMar 04 2025
R-4.5-macNOTEFeb 02 2025
R-4.5-linuxNOTEMar 04 2025
R-4.4-winOKMar 04 2025
R-4.4-macOKMar 04 2025
R-4.4-linuxOKMar 04 2025
R-4.3-winOKMar 04 2025
R-4.3-macOKMar 04 2025

Exports:calculate_vcsdo_bmaevaluate_modelsgam_model_probsplot_1d_smoothplot_2d_smooth

Dependencies:backportscachemcheckmateclassclassIntclicodetoolscolorspacecowplotcpp11data.tableDBIdigestdoParalleldplyre1071fansifarverfastmapforeachFormulaformula.toolsgenericsggplot2gluegtableisobanditeratorsKernSmoothlabelinglatticelifecyclelubridatemagrittrMASSMatrixmemoisemetRmgcvmunsellnlmeoperator.toolspillarpkgconfigplyrproxypurrrR6RColorBrewerRcpprlangs2scalessfstringistringrtibbletidyselecttimechangeunitsutf8vctrsviridisLitewithrwk

Determining Space-Time model form and Bayesian Model Avergaing (BMA) with stgam

Rendered fromspace-time-gam-model-probs-BMA.Rmdusingknitr::rmarkdownon Mar 04 2025.

Last update: 2024-10-10
Started: 2024-05-24

Introduction to space-time GAMS with stgam

Rendered fromspace-time-gam-intro.Rmdusingknitr::rmarkdownon Mar 04 2025.

Last update: 2025-01-03
Started: 2024-05-24