33 citations · 59 across the 25 of their papers we have counts for
6 papers · 1 filter
Statistical inference for Gaussian Whittle-Matérn fields on metric graphs
David Bolin, Alexandre Simas, Jonas Wallin
Whittle-Matérn fields are a recently introduced class of Gaussian processes on metric graphs, which are specified as solutions to a fractional-order stochastic differential equatio…
Efficient methods for Gaussian Markov random fields under sparse linear constraints
David Bolin, Jonas Wallin
Methods for inference and simulation of linearly constrained Gaussian Markov Random Fields (GMRF) are computationally prohibitive when the number of constraints is large. In some c…
Nonparametric Shrinkage Estimation in High Dimensional Generalized Linear Models via Polya Trees
Asaf Weinstein, Jonas Wallin, Daniel Yekutieli +1
Regularization in fitting regression models has been a highly active topic of research in the past few decades, but most of the existing methods are designed for particular situati…
Linear Mixed-Effects Models for Non-Gaussian Repeated Measurement Data
Özgür Asar, David Bolin, Peter J. Diggle +1
We consider the analysis of continuous repeated measurement outcomes that are collected through time, also known as longitudinal data. A standard framework for analysing data of th…
Level set Cox processes
Anders Hildeman, David Bolin, Jonas Wallin +1
The log-Gaussian Cox process (LGCP) is a popular point process for modeling non-interacting spatial point patterns. This paper extends the LGCP model to handle data exhibiting fund…
Multivariate type G Matérn stochastic partial differential equation random fields
David Bolin, Jonas Wallin
For many applications with multivariate data, random field models capturing departures from Gaussianity within realisations are appropriate. For this reason, we formulate a new cla…