Performance assessment of spatio-temporal regression kriging with GAMLSS models as trends
Author:
Affiliation:
1. Universidade Federal da Grande Dourados, Brazil
2. Universidade Federal da Lavras, Brazil
3. Universidade Estadual da Paraíba, Brazil
4. Universidade Federal de Campina Grande, Brazil
Publisher
FapUNIFESP (SciELO)
Subject
Multidisciplinary
Link
http://www.scielo.br/scielo.php?script=sci_pdf&pid=S0001-37652022000701104&tlng=en
Reference49 articles.
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2. Köppen’s climate classification map for Brazil;ALVARES CA;Meteorol Zeitschrift,2013
3. Conjuntura dos recursos hídricos no Brasil 2017: relatório pleno/Agência Nacional de Águas (ANA),2017
4. Rescaled range analysis of streamflow records in the São Francisco River Basin, Brazil;ARAUJO MVO;Theor Appl Climatol,2019
5. Gaussian Markov random field spatial models in GAMLSS;BASTIANI F;J Appl Stat,2018
Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Research Progress on Spatiotemporal Interpolation Methods for Meteorological Elements;Water;2024-03-11
2. Mapping Rainfall Variability in the São Francisco River Basin: Insights for Water Resource Management;Revista Brasileira de Meteorologia;2024
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