geoGAM
0.1-4Select Sparse Geoadditive Models for Spatial Prediction
Overview
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.
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- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 83%
- Documented parameters
- 33%
- Return-value docs
- 100%
- References docs
- 100%
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People & History
4 releases. Pick two to compare their code metrics. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- 0.1-4Latest
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- 0.1-32023-11-14 · diff ↗
- unarchivedReturned to CRAN2023-11-14
- RR 4.3.0 released · 2023-04-21
- archivedRemoved from CRAN2022-08-12email to the maintainer is undeliverable
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- RR 4.0.0 released · 2020-04-24
- RR 3.6.0 released · 2019-04-26
- RR 3.5.0 released · 2018-04-23
- 0.1-22017-07-23 · diff ↗
- RR 3.4.0 released · 2017-04-21
- 0.1-12016-10-29
Show 1 earlier events
- RR 3.3.0 released · 2016-05-03
Package metadata
- First published
- 2016-10-29
- Total releases
- 4 / 10 yrs
- License
- GPL (>= 2) OSI
- Minimum R
- ≥ 2.14.0
- Bundled data
- 3.1 MB / 3 files
- Download size
- 3.2 MB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet