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Provides tools for fitting spatial Mixed Data Sampling (MIDAS) regression models using Integrated Nested Laplace Approximation (INLA). The package is designed for settings where responses and explanatory variables are observed at different temporal frequencies and supports both constant and spatially varying regression coefficients.
| Version: | 0.1.0 |
| Depends: | R (≥ 4.2) |
| Imports: | matrixStats, Matrix, stats |
| Suggests: | INLA, knitr, rmarkdown, testthat (≥ 3.0.0), dplyr, ggplot2, tidyr |
| Published: | 2026-09-17 |
| DOI: | 10.32614/CRAN.package.midasINLA |
| Author: | Stephen Jun Villejo [aut, cre] |
| Maintainer: | Stephen Jun Villejo <s.villejo at imperial.ac.uk> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| Additional_repositories: | https://inla.r-inla-download.org/R/stable |
| Materials: | README |
| CRAN checks: | midasINLA results |
| Reference manual: | midasINLA.html , midasINLA.pdf |
| Vignettes: |
Getting started with midasINLA (source, R code) |
| Package source: | midasINLA_0.1.0.tar.gz |
| Windows binaries: | r-devel: not available, r-release: not available, r-oldrel: midasINLA_0.1.0.zip |
| macOS binaries: | r-release (arm64): midasINLA_0.1.0.tgz, r-oldrel (arm64): midasINLA_0.1.0.tgz, r-release (x86_64): midasINLA_0.1.0.tgz, r-oldrel (x86_64): midasINLA_0.1.0.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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