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Pages
Posts
Future Blog Post
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Blog Post number 4
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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 3
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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 2
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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 1
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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
portfolio
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publications
Robust estimation of a dynamic spatio-temporal model with structural change
Published in Journal of Statistical Computation and Simulation, 2016
Recommended citation: Villejo, S. J. V., Barrios, E. B., & Lansangan, J. R. G. (2017). Robust estimation of a dynamic spatio-temporal model with structural change. Journal of Statistical Computation and Simulation, 87(3), 505-518.
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An Analysis of the Impact of ASEAN Logistics Performance on Trade Flows Using Linear and Non-linear methods in an Augmented Gravity Model
Published in Logistics Research, 2020
Recommended citation: Sy, B., Villejo, S. J., & Lacazav, R. (2020). An analysis of the impact of ASEAN logistics performance on trade flows using linear and non-linear methods in an augmented gravity model. Logistics Research, 13(1), 1-22.
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Data fusion in a two-stage spatio-temporal model using the INLA-SPDE approach
Published in Spatial Statistics, 2023
Recommended citation: Villejo, S. J., Illian, J. B., & Swallow, B. (2023). Data fusion in a two-stage spatio-temporal model using the INLA-SPDE approach. Spatial Statistics, 54, 100744.
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Gaussian process for modelling the space environment from sparse data collected by massively distributed femtosatellite networks
Published in 75th International Astronautical Congress (IAC), Milan, Italy, 14 -- 18 October 2024, 2024
Recommended citation: Teale, C., Colombo, P., Villejo, S. J., & McInnes, C. (2024, October 14–18). Gaussian process for modelling the space environment from sparse data collected by massively distributed femtosatellite networks [Conference presentation]. 75th International Astronautical Congress (IAC), Milan, Italy.
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Validating uncertainty propagation approaches for two-stage Bayesian spatial models using simulation-based calibration
Published in arXiv, 2025
Recommended citation: Villejo, S. J., Martino, S., Illian, J., Ryan, W., & Lindgren, F. (2025). Validating uncertainty propagation approaches for two-stage Bayesian spatial models using simulation-based calibration. arXiv preprint arXiv:2502.18962.
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A data fusion model for meteorological data using the INLA-SPDE method
Published in Journal of the Royal Statistical Society Series C: Applied Statistics, 2025
Recommended citation: Villejo, S. J., Martino, S., Lindgren, F., & Illian, J. B. (2025). A data fusion model for meteorological data using the INLA-SPDE method. Journal of the Royal Statistical Society Series C: Applied Statistics, 74(4), 1021-1056.
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Linking climate and dengue in the Philippines using a two-stage Bayesian spatio-temporal model
Published in arXiv, 2025
Recommended citation: Villejo, S. J., Martino, S., & Illian, J. (2025). Linking climate and dengue in the Philippines using a two-stage Bayesian spatio-temporal model. arXiv preprint arXiv:2506.22334.
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Development of a clinical prediction model for the diagnosis of tuberculous pleural effusion in a resource-limited setting
Published in European Respiratory Journal , 2025
Recommended citation: Villanueva, C. A., Cruz, A. M., Cruz, K. M., Uy, T. C., Villejo, S. J., & Santiaguel, J. (2025). Development of a clinical prediction model for the diagnosis of tuberculous pleural effusion in a resource-limited setting. European Respiratory Journal, 66(Suppl 69), PA783. https://doi.org/10.1183/13993003.congress-2025.PA783
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Spatially continuous modelling of aggregated outcome data
Published in arxiv, 2026
Recommended citation: Villejo, S.J., Diggle, P., Lindgren, F., Rue, H., Li, G., White, E., Wade, M. and Blangiardo, M., 2026. Spatially continuous modelling of aggregated outcome data. arXiv preprint arXiv:2604.15452.
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talks
A data fusion model for meteorological data in the Philippines using the INLA-SPDE method
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Block aggregation modelling approach for spatial models
Published:
This work develops a spatial modelling approach for areal data when predictors are available at finer grid‑based resolutions. The method treats area‑level response data as aggregates of an underlying latent spatial process. The aggregation involves an appropriate functional depending on the likelihood or sampling model. The proposed method provides a unified framework for understanding response-covariate relationship, doing spatial disaggregation, and predicting the latent process at arbitrary block configurations. A simulation study evaluates performance under varying sampling proportions, spatial correlation ranges, and marginal variances, and compares the proposed block‑aggregation model with two alternatives: a traditional geostatistical modelling approach and a Markov random field (MRF) approach. Results show that for Gaussian data, the proposed approach and the first model comparator perform similarly, while the MRF performs poorly when spatial range is smaller than area size. For Poisson data, the proposed method yields more accurate latent‑field predictions and reduced parameter bias. Two real‑data applications illustrate the approaches: modelling wastewater viral concentrations across England during the COVID-19 pandemic using population density raster as covariate, and modelling the number of cardiovascular hospitalisations at local authority level in England using socio-demographic variables at fine-scale administrative units as covariates.
teaching
University of the Philippines
Lecture, School of Statistics, University of the Philippines Diliman, 0000
I taught several courses from 2013 to 2019 in my capacity as an Assistant Professor and Lecturer at the University of the Philippines Diliman.
University of Glasgow
Lecture, School of Mathematics and Statistics, College of Science and Engineering, 0000
I am doing lectures and tutorials in several courses both in the undergraduate and graduate programs from 2021 to 2025 as a MacLaurin Scholar.
Imperial College London
Lecture, School of Public Health, Faculty of Medicine, 0000
I am doing lectures in the course on Bayesian reasoning and methods for spatio-temporal data for Term 2 AY 2025-2026.