Statistics for climate informatics.
- Published in:
- Environmetrics, 2019, v. 30, n. 4, p. N.PAG, doi. 10.1002/env.2567
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- Publication type:
- Article
Works matching IS 11804009 AND DT 2019 AND VI 30 AND IP 4
Results: 10
1
2
A likelihood for correlated extreme series.
- Published in:
- Environmetrics, 2019, v. 30, n. 4, p. N.PAG, doi. 10.1002/env.2546
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- Publication type:
- Article
3
Estimating precipitation extremes using the log‐histospline.
- Published in:
- Environmetrics, 2019, v. 30, n. 4, p. N.PAG, doi. 10.1002/env.2543
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- Publication type:
- Article
4
A study of links between the Arctic and the midlatitude jet stream using Granger and Pearl causality.
- Published in:
- Environmetrics, 2019, v. 30, n. 4, p. N.PAG, doi. 10.1002/env.2540
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- Publication type:
- Article
5
Unsupervised space–time clustering using persistent homology.
- Published in:
- Environmetrics, 2019, v. 30, n. 4, p. N.PAG, doi. 10.1002/env.2539
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- Publication type:
- Article
6
Double‐structured sparse multitask regression with application of statistical downscaling.
- Published in:
- Environmetrics, 2019, v. 30, n. 4, p. N.PAG, doi. 10.1002/env.2534
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- Publication type:
- Article
7
Predictability assessment of northeast monsoon rainfall in India using sea surface temperature anomaly through statistical and machine learning techniques.
- Published in:
- Environmetrics, 2019, v. 30, n. 4, p. N.PAG, doi. 10.1002/env.2533
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- Publication type:
- Article
8
Increases in the extreme rainfall events: Using the Weibull distribution.
- Published in:
- Environmetrics, 2019, v. 30, n. 4, p. N.PAG, doi. 10.1002/env.2532
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- Publication type:
- Article
9
Predicting climate types for the Continental United States using unsupervised clustering techniques.
- Published in:
- Environmetrics, 2019, v. 30, n. 4, p. N.PAG, doi. 10.1002/env.2524
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- Publication type:
- Article
10
Issue Information.
- Published in:
- Environmetrics, 2019, v. 30, n. 4, p. N.PAG, doi. 10.1002/env.2514
- Publication type:
- Article