[aut,
cre],
Tim Lucas [aut],
Rohan Arambepola [aut],
Andre Python
[aut]Fits disaggregation regression models using 'TMB' ('Template Model Builder'). When the response data are aggregated to polygon level but the predictor variables are at a higher resolution, these models can be useful. Regression models with spatial random fields. A useful reference for disaggregation modelling is Lucas et al. (2019) <doi:10.1101/548719>.
| Version: | 0.1.3 |
| Imports: | maptools, raster, foreach, sp, parallel, doParallel, rgeos, splancs, rgdal, Matrix, stats, TMB, dplyr, ggplot2, cowplot, sparseMVN, utils |
| LinkingTo: | TMB, RcppEigen |
| Suggests: | testthat, INLA, knitr, rmarkdown, SpatialEpi |
| Published: | 2020-02-19 |
| Author: | Anita Nandi [aut,
cre],
Tim Lucas [aut],
Rohan Arambepola [aut],
Andre Python
[aut] |
| Maintainer: | Anita Nandi <anita.k.nandi at gmail.com> |
| License: | MIT + file LICENSE |
| NeedsCompilation: | yes |
| SystemRequirements: | GNU make |
| Citation: | disaggregation citation info |
| CRAN checks: | disaggregation results |
| Reference manual: | disaggregation.pdf |
| Vignettes: |
A short introduction to the disaggregation package |
| Package source: | disaggregation_0.1.3.tar.gz |
| Windows binaries: | r-devel: disaggregation_0.1.3.zip, r-release: disaggregation_0.1.3.zip, r-oldrel: disaggregation_0.1.3.zip |
| macOS binaries: | r-release: disaggregation_0.1.3.tgz, r-oldrel: disaggregation_0.1.3.tgz |
| Old sources: | disaggregation archive |
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