The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
A Generalized Linear Model Approach to Spatial Data Analysis and Prediction
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Citations
Cites
Quasi-likelihood functions, generalized linear models, and the Gauss—Newton method
WEDDERBURN, R. W. M. (1974) · Biometrika · doi:10.1093/biomet/61.3.439 · Cited by 2,122
Cited by
A generic framework for spatial prediction of soil variables based on regression-kriging
Hengl, T., Heuvelink, G. B. M., & Stein, A. (2004) · Geoderma · doi:10.1016/j.geoderma.2003.08.018 · Cited by 1,083
About regression-kriging: From equations to case studies
Hengl, T., Heuvelink, G. B. M., & Rossiter, D. G. (2007) · Computers & Geosciences · doi:10.1016/j.cageo.2007.05.001 · Cited by 1,019
Model-Based Geostatistics for Prevalence Mapping in Low-Resource Settings
Diggle, P. J., & Giorgi, E. (2016) · Journal of the American Statistical Association · doi:10.1080/01621459.2015.1123158 · Cited by 56
Metadata
- Authors
- Gotway, C. A., & Stroup, W. W.
- Venue
- Journal of Agricultural, Biological, and Environmental Statistics
- Published
- 1997-06
- Volume
- 2
- Issue
- 2
- Pages
- 157
- ISSN
- 1085-7117 (ISSN-L)
- OpenAlex
- W2059215788
- Cited by
- 191
- References
- 1
- FWCI
- 7.32
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: A Generalized Linear Model Approach to Spatial Data Analysis and Prediction. https://app.cochat.ai/papers/10.2307/1400401
- The paper
- Gotway, C. A., & Stroup, W. W. (1997). A Generalized Linear Model Approach to Spatial Data Analysis and Prediction. Journal of Agricultural, Biological, and Environmental Statistics. https://doi.org/10.2307/1400401
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
