DOI zum Zitieren der Version auf EPub Bayreuth: https://doi.org/10.15495/EPub_UBT_00007291
URN to cite this document: urn:nbn:de:bvb:703-epub-7291-8
URN to cite this document: urn:nbn:de:bvb:703-epub-7291-8
Title data
Lu, Meng ; Cavieres, Joaquin ; Moraga, Paula:
A Comparison of Spatial and Nonspatial Methods in Statistical Modeling of NO₂ : Prediction Accuracy, Uncertainty Quantification, and Model Interpretation.
In: Geographical Analysis.
Vol. 55
(2023)
Issue 4
.
- pp. 703-727.
ISSN 1538-4632
DOI der Verlagsversion: https://doi.org/10.1111/gean.12356
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Further data
Item Type: | Article in a journal |
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DDC Subjects: | 500 Science > 550 Earth sciences, geology |
Institutions of the University: | Faculties > Faculty of Biology, Chemistry and Earth Sciences > Department of Earth Sciences > Juniorprofessur Geoinformatik - Spatial Big Data > Juniorprofessur Geoinformatik - Spatial Big Data - Juniorprof. Dr. Meng Lu Faculties Faculties > Faculty of Biology, Chemistry and Earth Sciences Faculties > Faculty of Biology, Chemistry and Earth Sciences > Department of Earth Sciences Faculties > Faculty of Biology, Chemistry and Earth Sciences > Department of Earth Sciences > Juniorprofessur Geoinformatik - Spatial Big Data |
Language: | English |
Originates at UBT: | Yes |
URN: | urn:nbn:de:bvb:703-epub-7291-8 |
Date Deposited: | 08 Nov 2023 10:20 |
Last Modified: | 08 Nov 2023 10:21 |
URI: | https://epub.uni-bayreuth.de/id/eprint/7291 |