18 citations · 39 across the 7 of their papers we have counts for
8 papers
Bayesian identification of early warning signals for long-range dependent climatic time series
Sigrunn H. Sørbye, Eirik Myrvoll-Nilsen, Håvard Rue
Detecting early warning signals in climatic time series is essential for anticipating critical transitions and tipping points. Common statistical indicators include increased varia…
Seasonality, density dependence and spatial population synchrony
Pedro G Nicolau, Sigrunn H Sørbye, Nigel G Yoccoz +1
Spatial population synchrony has been the focus of theoretical and empirical studies for decades, in the hopes of understanding mechanisms and interactions driving ecological dynam…
Model-based bias correction for short AR(1) and AR(2) processes
Sigrunn H. Sørbye, Pedro G. Nicolau, Håvard Rue
The class of autoregressive (AR) processes is extensively used to model temporal dependence in observed time series. Such models are easily available and routinely fitted using fre…
An approximate fractional Gaussian noise model with computational cost
Sigrunn H. Sørbye, Eirik Myrvoll-Nilsen, Håvard Rue
Fractional Gaussian noise (fGn) is a stationary time series model with long memory properties applied in various fields like econometrics, hydrology and climatology. The computatio…
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…
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-…
Going off grid: Computationally efficient inference for log-Gaussian Cox processes
Daniel Simpson, Janine Illian, Finn Lindgren +2
This paper introduces a new method for performing computational inference on log-Gaussian Cox processes. The likelihood is approximated directly by making novel use of a continuous…