geoGAM
type: Item
instance of: R package
description: 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>.
last update: 2023-11-14T00:00:00Z
software version identifier: 0.1-1
software version identifier: 0.1-2
software version identifier: 0.1-3
author: Madlene Nussbaum
maintained by: Madlene Nussbaum
copyright license: GNU General Public License, version 2.0
copyright license: GNU General Public License, version 3.0
imports: mboost
imports: mgcv
imports: grpreg
imports: MASS
cites work: Mapping of soil properties at high resolution in Switzerland using boosted geoadditive models
CRAN project: geoGAM
programmed in: R
depends on software: R
MaRDI profile type: Software
description: Select Sparse Geoadditive Models for Spatial Prediction