Publications

Full publication list

Publications by statistician Daniela Castro-Camilo on environmental extremes, spatial statistics, Bayesian modelling, causal inference and risk.

This page lists publications by year, including manuscripts under revision. Topic links point to the research areas where each paper fits most naturally.

2026

  1. Hu, C., Bispo, R. B., Rue, H., DaCamara, C. C., Swallow, B. and Castro-Camilo, D. (2026). XGBoost meets INLA: a two-stage spatio-temporal forecasting of wildfires in Portugal. Environmetrics, 37(3), e70089. DOI: 10.1002/env.70089.
    Topics: Spatial extremes, INLA/SPDE, Ecology & environment, Data fusion

  2. Maia, M., Castro-Camilo, D. and Browell, J. (2026). Probabilistic forecasting of weather-driven faults in electricity networks: a flexible approach for extreme and non-extreme events. Technometrics. Early online publication. DOI: 10.1080/00401706.2026.2649039.
    Topics: Energy risk, Tail modelling

  3. Li, M., & Castro-Camilo, D. (2026). On the importance of tail assumptions in climate extreme event attribution. arXiv preprint arXiv:2507.14019.
    Topics: Causality, Tail modelling, Risk assessment, Ecology & environment

  4. Li, M., & Castro-Camilo, D. (2026). Tail-Calibrated Estimation of Extreme Quantile Treatment Effects. arXiv preprint arXiv:2603.23309.
    Topics: Causality, Tail modelling, Risk assessment

  5. Li, M., & Castro-Camilo, D. (2026). Causal Discovery in Multivariate Extremes via Tail Asymmetry. arXiv preprint arXiv:2604.21620.
    Topics: Causality, Tail modelling, Risk assessment

  6. Shen, T., Browell, J., & Castro-Camilo, D. (2026). Adaptive Bayesian Very Short-Term Wind Power Forecasting Based on the Generalised Logit Transformation. arXiv preprint arXiv:2505.06310.
    Topics: Energy risk, Risk assessment

  7. Hu, C., Swallow, B., & Castro-Camilo, D. (2026). A Bayesian multivariate extreme value mixture model. arXiv preprint arXiv:2401.15703.
    Topics: Tail modelling, Risk assessment

  8. Cuba, M. D., Wilkie, C., Scott, M., & Castro-Camilo, D. (2026). Spatio-temporal data fusion of censored threshold exceedances. arXiv preprint arXiv:2504.20268.
    Topics: Data fusion, Tail modelling, Ecology & environment

2025

  1. Li, M., Cuba, D., Hu, C. and Castro-Camilo, D. (2025). A wee exploration of techniques for risk assessments of extreme events. Extremes, 28(1), 101–121. DOI: 10.1007/s10687-024-00500-5.
    Topics: Risk assessment, Ecology & environment

  2. Bryce, E., Castro-Camilo, D., Dashwood, C., Tanyas, H., Ciurean, R., Novellino, A. and Lombardo, L. (2025). An updated landslide susceptibility model and a log-Gaussian Cox process extension for Scotland. Landslides, 22(2), 517–535. DOI: 10.1007/s10346-024-02368-9.
    Topics: Landslide hazard, INLA/SPDE, Risk assessment

  3. Hu, C., & Castro-Camilo, D. (2025). GPDFlow: Generative multivariate threshold exceedance modeling via normalizing flows. arXiv preprint arXiv:2503.11822.
    Topics: , Tail modelling, Risk assessment

2023

  1. Di Napoli, M., Tanyas, H., Castro-Camilo, D., Calcaterra, D., Cevasco, A., Di Martire, D., Pepe, G., Brandolini, P. and Lombardo, L. (2023). On the estimation of landslide intensity, hazard and density via data-driven models. Natural Hazards, 119(3), 1513–1530. DOI: 10.1007/s11069-023-06153-0.
    Topics: Landslide hazard

  2. Novellino, A., Ciurean, R., Bryce, E., Castro-Camilo, D. and Lombardo, L. (2023). Mitigating Landslides Impact in Scotland - MLIS. Summary Report. National Centre for Resilience.
    Topics: Landslide hazard, Risk assessment

2022

  1. Castro-Camilo, D., Huser, R. and Rue, H. (2022). Practical strategies for GEV-based regression models for extremes. Environmetrics, 33(6), e2742. DOI: 10.1002/env.2742.
    Topics: Spatial extremes, Tail modelling, INLA/SPDE

  2. Bryce, E., Lombardo, L., van Westen, C., Tanyas, H. and Castro-Camilo, D. (2022). Unified landslide hazard assessment using hurdle models: a case study in the Island of Dominica. Stochastic Environmental Research and Risk Assessment, 36(8), 2071–2084. DOI: 10.1007/s00477-022-02239-6.
    Topics: Landslide hazard, Risk assessment

  3. Vandeskog, S. M., Martino, S., Castro-Camilo, D., & Rue, H. (2022). Modelling sub-daily precipitation extremes with the blended generalised extreme value distribution. Journal of Agricultural, Biological and Environmental Statistics, 27(4), 598-621.
    Topics: Tail modelling, Ecology & environment

2021

  1. Lombardo, L., Tanyas, H., Huser, R., Guzzetti, F. and Castro-Camilo, D. (2021). Landslide size matters: a new data-driven, spatial prototype. Engineering Geology, 293, 106288. DOI: 10.1016/j.enggeo.2021.106288.
    Topics: Landslide hazard

  2. Vandeskog, S. M., Martino, S. and Castro-Camilo, D. (2021). Modelling Block Maxima With the Blended Generalised Extreme Value Distribution. 22nd European Young Statisticians Meeting.
    Topics: Tail modelling

  3. Castro-Camilo, D., Mhalla, L. and Opitz, T. (2021). Bayesian space-time gap filling for inference on extreme hot-spots: an application to Red Sea surface temperatures. Extremes, 24(1), 105–128. DOI: 10.1007/s10687-020-00394-z.
    Topics: Spatial extremes, Data fusion, Ecology & environment

2020

  1. Castro-Camilo, D. and Huser, R. (2020). Local likelihood estimation of complex tail dependence structures, applied to U.S. precipitation extremes. Journal of the American Statistical Association, 115(531), 1037–1054. DOI: 10.1080/01621459.2019.1647842.
    Topics: Spatial extremes, Tail modelling, Risk assessment

2019

  1. Amato, G., Eisank, C., Castro-Camilo, D. and Lombardo, L. (2019). Accounting for covariate distributions in slope-unit-based landslide susceptibility models. A case study in the alpine environment. Engineering Geology, 260, 105237. DOI: 10.1016/j.enggeo.2019.105237.
    Topics: Landslide hazard

  2. Castro-Camilo, D., Huser, R. and Rue, H. (2019). A spliced Gamma-Generalized Pareto model for short-term extreme wind speed probabilistic forecasting. Journal of Agricultural, Biological and Environmental Statistics, 24(3), 517–534. DOI: 10.1007/s13253-019-00369-z.
    Topics: Energy risk, Tail modelling, INLA/SPDE

2018

  1. Krainski, E. T., Gómez-Rubio, V., Bakka, H., Lenzi, A., Castro-Camilo, D., Simpson, D., Lindgren, F. and Rue, H. (2018). Advanced Spatial Modeling With Stochastic Partial Differential Equations Using R and INLA. Chapman & Hall/CRC. DOI: 10.1201/9780429031892.
    Topics: INLA/SPDE, Spatial extremes

  2. Bakka, H. C., Castro-Camilo, D., Franco-Villoria, M., Freni-Sterrantino, A., Huser, T. and Rue, H. (2018). Contributed discussion of “Using Stacking to Average Bayesian Predictive Distributions” by Yao et al. Bayesian Analysis, 13(3), 982–985. DOI: 10.1214/17-BA1091.
    Topics: INLA/SPDE, Bayesian modelling

  3. Castro-Camilo, D., de Carvalho, M. and Wadsworth, J. (2018). Time-varying extreme value dependence with application to leading European stock markets. Annals of Applied Statistics, 12(1), 283–309. DOI: 10.1214/17-AOAS1089.
    Topics: Tail modelling, Risk assessment

2017

  1. Castro-Camilo, D., Lombardo, L., Mai, P. M., Dou, J. and Huser, R. (2017). Handling high predictor dimensionality in slope-unit-based landslide susceptibility models through LASSO-penalized Generalized Linear Model. Environmental Modelling and Software, 97, 145–156. DOI: 10.1016/j.envsoft.2017.08.003.
    Topics: Landslide hazard

  2. Castro-Camilo, D. and de Carvalho, M. (2017). Spectral density regression for bivariate extremes. Stochastic Environmental Research and Risk Assessment, 31(7), 1603–1613. DOI: 10.1007/s00477-016-1257-z.
    Topics: Tail modelling, Risk assessment