2003/01/01 by E. E. Kammann, M. P. Wand · 1 citation
Environmental Science · Mathematics · #Soil Geostatistics and Mapping #Statistical Methods and Bayesian Inference #Statistical Methods and Inference
paper · pdf · doi:10.1111/1467-9876.00385
crossref issued 2003/01/01 · crossref published 2003/01/01 · crossref published-print 2003/01/01 · openalex publication_date 2003/01/01 · crossref published-online 2003/01/08 · crossref created 2003/03/12 · openalex created_date 2022/05/12 · crossref deposited 2024/01/09 · crossref indexed 2026/07/29 · openalex updated_date 2026/07/29
Summary A study into geographical variability of reproductive health outcomes (e.g. birth weight) in Upper Cape Cod, Massachusetts, USA, benefits from geostatistical mapping or kriging. However, also observed are some continuous covariates (e.g. maternal age) that exhibit pronounced non-linear relationships with the response variable. To account for such effects properly we merge kriging with additive models to obtain what we call geoadditive models. The merging becomes effortless by expressing both as linear mixed models. The resulting mixed model representation for the geoadditive model allows for fitting and diagnosis using standard methodology and software.