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A model building procedure to build parsimonious geoadditive model from a large number of covariates. Continuous, binary and ordered categorical responses are supported. The model building is based on component wise gradient boosting with linear effects, smoothing splines and a smooth spatial surface to model spatial autocorrelation. The resulting covariate set after gradient boosting is further reduced through backward elimination and aggregation of factor levels. The package provides a model based bootstrap method to simulate prediction intervals for point predictions. A test data set of a soil mapping case study in Berne (Switzerland) is provided. Nussbaum, M., Walthert, L., Fraefel, M., Greiner, L., and Papritz, A. (2017) <doi:10.5194/soil-3-191-2017>.
| Version: | 0.1-3 |
| Depends: | R (≥ 2.14.0) |
| Imports: | mboost, mgcv, grpreg, MASS |
| Suggests: | raster, sp |
| Published: | 2023-11-14 |
| DOI: | 10.32614/CRAN.package.geoGAM |
| Author: | Madlene Nussbaum [cre, aut], Andreas Papritz [ths] |
| Maintainer: | Madlene Nussbaum <m.nussbaum at uu.nl> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| CRAN checks: | geoGAM results |
| Reference manual: | geoGAM.pdf |
| Package source: | geoGAM_0.1-3.tar.gz |
| Windows binaries: | r-devel: geoGAM_0.1-3.zip, r-release: geoGAM_0.1-3.zip, r-oldrel: geoGAM_0.1-3.zip |
| macOS binaries: | r-release (arm64): geoGAM_0.1-3.tgz, r-oldrel (arm64): geoGAM_0.1-3.tgz, r-release (x86_64): geoGAM_0.1-3.tgz, r-oldrel (x86_64): geoGAM_0.1-3.tgz |
| Old sources: | geoGAM archive |
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