On the second-order random walk model for irregular locations

Finn Lindgren*, Haavard Rue

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

44 Scopus citations

Abstract

The second-order random walk (RW2) model is commonly used for smoothing data and for modelling response functions. It is computationally efficient due to the Markov properties of the joint (intrinsic) Gaussian density. For evenly spaced locations the RW2 model is well established, whereas for irregularly spaced locations there is no well established construction in the literature. By considering the RW2 model as the solution of a stochastic differential equation (SDE), a discretely observed integrated Wiener process, it is possible to derive the density preserving the Markov properties by augmenting the state-space with the velocities. Here, we derive a computationally more efficient RW2 model for irregular locations using a Galerkin approximation to the solution of the SDE without the need of augmenting the state-space. Numerical comparison with the exact solution demonstrates that the error in the Galerkin approximation is small and negligible in applications.

Original languageEnglish (US)
Pages (from-to)691-700
Number of pages10
JournalScandinavian Journal of Statistics
Volume35
Issue number4
DOIs
StatePublished - Dec 1 2008

Keywords

  • Galerkin approximation
  • Integrated Wiener process
  • Intrinsic Gaussian Markov random fields
  • Numerical methods for sparse matrices
  • Second-order random walk

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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