Blar i NTNU Open på forfatter "Sørbye, Sigrunn Holbek"
-
A toolbox for fitting complex spatial point process models using integrated nested Laplace approximation (INLA)
Illian, Janine; Sørbye, Sigrunn Holbek; Rue, Håvard (Journal article; Peer reviewed, 2012) -
Bayesian Computing with INLA: A Review
Rue, Håvard; Riebler, Andrea Ingeborg; Sørbye, Sigrunn Holbek; Illian, Janine B.; Simpson, Daniel Peter; Lindgren, Finn Kristian (Journal article; Peer reviewed, 2017)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-Simon Laplace (1774). This simple idea ... -
Modeling Solar Orbiter dust detection rates in the inner heliosphere as a Poisson process
Kociscak, Samuel; Kvammen, Andreas; Mann, Ingrid; Sørbye, Sigrunn Holbek; Theodorsen, Audun; Zaslavsky, Arnaud (Peer reviewed; Journal article, 2023)Context. Solar Orbiter provides dust detection capability in the inner heliosphere, but estimating physical properties of detected dust from the collected data is far from straightforward. Aims. First, a physical model ... -
Penalising Model Component Complexity: A Principled, Practical Approach to Constructing Priors
Simpson, Daniel; Rue, Håvard; Riebler, Andrea Ingeborg; Martins, Thiago Guerrera; Sørbye, Sigrunn Holbek (Journal article; Peer reviewed, 2017)In this paper, we introduce a new concept for constructing prior distributions. We exploit the natural nested structure inherent to many model components, which defines the model component to be a flexible extension of a ... -
You Just Keep on Pushing My Love over the Borderline: A Rejoinder
Simpson, Daniel; Rue, Håvard; Riebler, Andrea Ingeborg; Martins, Thiago Guerrera; Sørbye, Sigrunn Holbek (Journal article; Peer reviewed, 2017)The entire reason that we wrote this paper was to provide a concrete object around which to focus a broader discussion about prior choice and we are extremely grateful to the editorial team at Statistical Science for this ...