Quantifying the uncertainty of contour maps
Journal article, 2017

Contour maps are widely used to display estimates of spatial fields. Instead of showing the estimated field, a contour map only shows a fixed number of contour lines for different levels. However, despite the ubiquitous use of these maps, the uncertainty associated with them has been given a surprisingly small amount of attention. We derive measures of the statistical uncertainty, or quality, of contour maps, and use these to decide an appropriate number of contour lines, that relates to the uncertainty in the estimated spatial field. For practical use in geostatistics and medical imaging, computational methods are constructed, that can be applied to Gaussian Markov random fields, and in particular be used in combination with integrated nested Laplace approximations for latent Gaussian models. The methods are demonstrated on simulated data and an application to temperature estimation is presented.

Author

David Bolin

Chalmers, Mathematical Sciences, Mathematical Statistics

University of Gothenburg

Finn Lindgren

University of Bath

Journal of Computational and Graphical Statistics

1061-8600 (ISSN) 1537-2715 (eISSN)

Vol. 26 3 513-524

Subject Categories

Mathematics

Probability Theory and Statistics

DOI

10.1080/10618600.2016.1228537

More information

Latest update

3/5/2020 1