63 citations · 227 across the 34 of their papers we have counts for
5 papers · 1 filter
Fractional Gaussian noise: Prior specification and model comparison
Sigrunn Holbek Sørbye, Håvard Rue
Fractional Gaussian noise (fGn) is a self-similar stochastic process used to model anti-persistent or persistent dependency structures in observed time series. Properties of the au…
Penalised complexity priors for stationary autoregressive processes
Sigrunn Holbek Sørbye, Håvard Rue
The autoregressive process of order (AR()) is a central model in time series analysis. A Bayesian approach requires the user to define a prior distribution for the coefficie…
Non-stationary Gaussian models with physical barriers
Haakon Bakka, Jarno Vanhatalo, Janine Illian +2
The classical tools in spatial statistics are stationary models, like the Matérn field. However, in some applications there are boundaries, holes, or physical barriers in the study…
Bayesian Computing with INLA: A Review
Håvard Rue, Andrea Riebler, Sigrunn H. Sørbye +3
The key operation in Bayesian inference, is to compute high-dimensional integrals. An old approximate technique is the Laplace method or approximation, which dates back to Pierre-…
An intuitive Bayesian spatial model for disease mapping that accounts for scaling
Andrea Riebler, Sigrunn H. Sørbye, Daniel Simpson +1
In recent years, disease mapping studies have become a routine application within geographical epidemiology and are typically analysed within a Bayesian hierarchical model formulat…