Search Results for author: Finn Lindgren

Found 5 papers, 0 papers with code

The Integrated Nested Laplace Approximation for fitting Dirichlet regression models

no code implementations9 Jul 2019 Joaquín Martínez-Minaya, Finn Lindgren, Antonio López-Quílez, Daniel Simpson, David Conesa

This paper introduces a Laplace approximation to Bayesian inference in Dirichlet regression models, which can be used to analyze a set of variables on a simplex exhibiting skewness and heteroscedasticity, without having to transform the data.

Bayesian Inference Computation Methodology

Spatial 3D Matérn priors for fast whole-brain fMRI analysis

no code implementations25 Jun 2019 Per Sidén, Finn Lindgren, David Bolin, Anders Eklund, Mattias Villani

Bayesian whole-brain functional magnetic resonance imaging (fMRI) analysis with three-dimensional spatial smoothing priors have been shown to produce state-of-the-art activity maps without pre-smoothing the data.

Methodology Applications Computation

Estimation of a non-stationary model for annual precipitation in southern Norway using replicates of the spatial field

no code implementations8 Dec 2014 Rikke Ingebrigtsen, Finn Lindgren, Ingelin Steinsland, Sara Martino

Estimation of stationary dependence structure parameters using only a single realisation of the spatial process, typically leads to inaccurate estimates and poorly identified parameters.

Methodology Applications

Does non-stationary spatial data always require non-stationary random fields?

no code implementations2 Sep 2014 Geir-Arne Fuglstad, Daniel Simpson, Finn Lindgren, Håvard Rue

A stationary spatial model is an idealization and we expect that the true dependence structures of physical phenomena are spatially varying, but how should we handle this non-stationarity in practice?

Methodology Applications

Exploring a New Class of Non-stationary Spatial Gaussian Random Fields with Varying Local Anisotropy

no code implementations25 Apr 2013 Geir-Arne Fuglstad, Finn Lindgren, Daniel Simpson, Håvard Rue

This allows for the introduction of parameters that control the GRF by parametrizing the diffusion matrix.

Methodology

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