Spatio‐temporal models for big multinomial data using the conditional multivariate logit‐beta distribution.
- Published in:
- Journal of Time Series Analysis, 2019, v. 40, n. 3, p. 363, doi. 10.1111/jtsa.12468
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- Publication type:
- Article
Works matching IS 01439782 AND DT 2019 AND VI 40 AND IP 3
Results: 8
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2
Recent Advances in Spatio‐Temporal Methodology.
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- Journal of Time Series Analysis, 2019, v. 40, n. 3, p. 267, doi. 10.1111/jtsa.12467
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- Publication type:
- Article
3
A Structural‐Factor Approach to Modeling High‐Dimensional Time Series and Space‐Time Data.
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- Journal of Time Series Analysis, 2019, v. 40, n. 3, p. 343, doi. 10.1111/jtsa.12466
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- Publication type:
- Article
4
Scalable inference for space‐time Gaussian Cox processes.
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- Journal of Time Series Analysis, 2019, v. 40, n. 3, p. 269, doi. 10.1111/jtsa.12457
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- Publication type:
- Article
5
On a Semiparametric Data‐Driven Nonlinear Model with Penalized Spatio‐Temporal Lag Interactions.
- Published in:
- Journal of Time Series Analysis, 2019, v. 40, n. 3, p. 327, doi. 10.1111/jtsa.12442
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- Publication type:
- Article
6
A Non‐Gaussian Spatio‐Temporal Model for Daily Wind Speeds Based on a Multi‐Variate Skew‐t Distribution.
- Published in:
- Journal of Time Series Analysis, 2019, v. 40, n. 3, p. 312, doi. 10.1111/jtsa.12437
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- Publication type:
- Article
7
Estimating Spatial Changes Over Time of Arctic Sea Ice using Hidden 2×2 Tables.
- Published in:
- Journal of Time Series Analysis, 2019, v. 40, n. 3, p. 288, doi. 10.1111/jtsa.12425
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- Publication type:
- Article
8
Issue Information.
- Published in:
- Journal of Time Series Analysis, 2019, v. 40, n. 3, p. 265, doi. 10.1111/jtsa.12413
- Publication type:
- Article