9 citations · 21 across the 4 of their papers we have counts for
4 papers
Multivariate Gaussian Random Fields with Oscillating Covariance Functions using Systems of Stochastic Partial Differential Equations
Xiangping Hu, Finn Lindgren, Daniel Simpson +1
In this paper we propose a new approach for constructing \emph{multivariate} Gaussian random fields (GRFs) with oscillating covariance functions through systems of stochastic parti…
Spatial Modelling of Temperature and Humidity using Systems of Stochastic Partial Differential Equations
Xiangping Hu, Ingelin Steinsland, Daniel Simpson +2
This work is motivated by constructing a weather simulator for precipitation. Temperature and humidity are two of the most important driving forces of precipitation, and the strate…
Bayesian Adaptive Smoothing Spline using Stochastic Differential Equations
Yu Ryan Yue, Daniel Simpson, Finn Lindgren +1
The smoothing spline is one of the most popular curve-fitting methods, partly because of empirical evidence supporting its effectiveness and partly because of its elegant mathemati…
Parameter estimation in high dimensional Gaussian distributions
Erlend Aune, Daniel P. Simpson
In order to compute the log-likelihood for high dimensional spatial Gaussian models, it is necessary to compute the determinant of the large, sparse, symmetric positive definite pr…