Spatiotemporal wildfire modeling through point processes with moderate and extreme marks-Reference-Cited by-同舟云学术

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Spatiotemporal wildfire modeling through point processes with moderate and extreme marks

Published:2023-03-01 Issue:1 Volume:17 Page:
ISSN:1932-6157
Container-title:The Annals of Applied Statistics
language:
Short-container-title:Ann. Appl. Stat.

Author:

Koh Jonathan¹,Pimont François²,Dupuy Jean-Luc²,Opitz Thomas³

Affiliation:

1. Institute of Mathematics, EPFL

2. URFM UR629, INRAE

3. BioSP UR546, INRAE

Publisher

Institute of Mathematical Statistics

Subject

Statistics, Probability and Uncertainty,Modeling and Simulation,Statistics and Probability

Reference59 articles.

1. FUGLSTAD, G.-A., SIMPSON, D., LINDGREN, F. and RUE, H. (2019). Constructing priors that penalize the complexity of Gaussian random fields. J. Amer. Statist. Assoc. 114 445–452.

2. DAVISON, A. C. and SMITH, R. L. (1990). Models for exceedances over high thresholds. J. Roy. Statist. Soc. Ser. B 52 393–442.

3. FAWCETT, T. (2006). An introduction to ROC analysis. Pattern Recogn. Lett. 27 861–874.

4. TIERNEY, L. and KADANE, J. B. (1986). Accurate approximations for posterior moments and marginal densities. J. Amer. Statist. Assoc. 81 82–86.

5. ILLIAN, J. B., SØRBYE, S. H. and RUE, H. (2012). A toolbox for fitting complex spatial point process models using integrated nested Laplace approximation (INLA). Ann. Appl. Stat. 6 1499–1530.

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