Statistical Modeling Using Bayesian Latent Gaussian Models

Dr. Birgir Hrafnkelsson is Professor of Statistics at the University of Iceland. He is an expert in computation for Bayesian latent Gaussian models, spatial statistics, spatio-temporal models, and applications of Bayesian latent Gaussian models in geophysics and environmental sciences. He has worked with experts in glaciology, seismology, engineering seismology, hydrology, meteorology and climatology. His research projects include; fast inference methods for latent Gaussian models; physical-statistical modeling of glacier dynamics; statistical ground motion models for seismic intensity measures; construction of discharge rating curves in open channel flow that make use of the underlying physics; statistical postprocessing for weather forecasting; and statistical models for spatial extremes with applications to temperature, precipitation and flood data.

Preface.- Chapter 1. Birgir Hrafnkelsson and Haakon Bakka: Bayesian latent Gaussian models.- Chapter 2. Giri Gopalan, Andrew Zammit-Mangion, and Felicity McCormack: A review of Bayesian modelling in glaciology.- Chapter 3. Birgir Hrafnkelsson, Rafael Daniel Vias, Solvi Rognvaldsson, Axel Orn Jansson, and Sigurdur M. Gardarsson: Bayesian discharge rating curves based on the generalized power law.- Chapter 4. Sahar Rahpeyma, Milad Kowsari, Tim Sonnemann, Benedikt Halldorsson, and Birgir Hrafnkelsson: Bayesian modeling in engineering seismology: Ground-motion models.- Chapter 5.  Atefe Darzi, Birgir Hrafnkelsson, and Benedikt Halldorsson: Bayesian modelling in engineering seismology: Spatial earthquake magnitude model.- Chapter 6. Joshua Lovegrove and Stefan Siegert: Improving numerical weather forecasts by Bayesian hierarchical modelling.- Chapter 7. Arnab Hazra, Raphael Huser, and Arni V. Johannesson: Bayesian latent Gaussian models for high-dimensional spatial extremes.