Benchmark dose risk analysis with mixed‐factor quantal data in environmental risk assessment.
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- Environmetrics, 2021, v. 32, n. 5, p. 1, doi. 10.1002/env.2677
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- Publication type:
- Article
Works matching IS 11804009 AND DT 2021 AND VI 32 AND IP 5
Results: 6
1
2
Comparing estimation of the parameters of distribution of the root density of plants in the presence of outliers.
- Published in:
- Environmetrics, 2021, v. 32, n. 5, p. 1, doi. 10.1002/env.2676
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- Publication type:
- Article
3
Spatial deformation for nonstationary extremal dependence.
- Published in:
- Environmetrics, 2021, v. 32, n. 5, p. 1, doi. 10.1002/env.2671
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- Publication type:
- Article
4
Flexible nonstationary spatiotemporal modeling of high‐frequency monitoring data.
- Published in:
- Environmetrics, 2021, v. 32, n. 5, p. 1, doi. 10.1002/env.2670
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- Publication type:
- Article
5
Identifying meteorological drivers of PM<sub>2.5</sub> levels via a Bayesian spatial quantile regression.
- Published in:
- Environmetrics, 2021, v. 32, n. 5, p. 1, doi. 10.1002/env.2669
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- Publication type:
- Article
6
Issue Information.
- Published in:
- Environmetrics, 2021, v. 32, n. 5, p. 1, doi. 10.1002/env.2637
- Publication type:
- Article