|Themes||Biostatistics; Computational Statistics; General Theory and Methodology; Multivariate and High Dimensional Data.|
Javier Rubio is a Lecturer in the Department of Statistical Science at University College London. He joined the Department in April 2021, and previously was a Lecturer in Statistics in the Department of Mathematics at King's College London. Before that, he was a Research Fellow at the London School of Hygiene and Tropical Medicine and the University of Warwick. He has a PhD in Statistics from the University of Warwick.
Bayesian Statistics, Objective Bayes, Model Selection, Survival Models, Longitudinal Models, Flexible distributions, Biostatistics.
- Rubio, F. J., & Steel, M. F. (2014). Inference in two-piece location-scale models with Jeffreys priors. Bayesian Analysis, 9(1), 1-22.
- Rossell, D., & Rubio, F. J. (2018). Tractable Bayesian variable selection: beyond normality. Journal of the American Statistical Association, 113(524), 1742-1758.
- Rubio, F. J., Remontet, L., Jewell, N. P., & Belot, A. (2019). On a general structure for hazard-based regression models: an application to population-based cancer research. Statistical methods in medical research, 28(8), 2404-2417.
- Rubio, F. J., Rachet, B., Giorgi, R., Maringe, C., & Belot, A. (2021). On models for the estimation of the excess mortality hazard in case of insufficiently stratified life tables. Biostatistics, 22(1), 51-67.
- Rubio, F.J. and Alvares, D. (2021). A tractable Bayesian joint model for longitudinal and survival data, with D. Alvares. Statistics in Medicine, in press.