Bias correction of daily precipitation from climate models, using the Q‐GAM method.
- Published in:
- Environmetrics, 2024, v. 35, n. 7, p. 1, doi. 10.1002/env.2881
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- Publication type:
- Article
Works matching IS 11804009 AND DT 2024 AND VI 35 AND IP 7
Results: 7
1
2
A hierarchical constrained density regression model for predicting cluster‐level dose‐response.
- Published in:
- Environmetrics, 2024, v. 35, n. 7, p. 1, doi. 10.1002/env.2880
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- Publication type:
- Article
3
A flexible and interpretable spatial covariance model for data on graphs.
- Published in:
- Environmetrics, 2024, v. 35, n. 7, p. 1, doi. 10.1002/env.2879
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- Publication type:
- Article
4
How to find the best sampling design: A new measure of spatial balance.
- Published in:
- Environmetrics, 2024, v. 35, n. 7, p. 1, doi. 10.1002/env.2878
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- Publication type:
- Article
5
Anthropogenic and meteorological effects on the counts and sizes of moderate and extreme wildfires.
- Published in:
- Environmetrics, 2024, v. 35, n. 7, p. 1, doi. 10.1002/env.2873
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- Publication type:
- Article
6
Marginal inference for hierarchical generalized linear mixed models with patterned covariance matrices using the Laplace approximation.
- Published in:
- Environmetrics, 2024, v. 35, n. 7, p. 1, doi. 10.1002/env.2872
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- Publication type:
- Article
7
Issue Information.
- Published in:
- Environmetrics, 2024, v. 35, n. 7, p. 1, doi. 10.1002/env.2813
- Publication type:
- Article